AbstractBackgroundGlioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments.MethodsWe collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV).ResultsWe collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32).ConclusionMRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology.
Abstract 4714: The association of glioma germline risk SNPs with mutation-based molecular subgroups
Abstract Background: Specific germline alterations within the TERT, EGFR, CCDC26, CDKN2A/B, PHLDB1, TP53 and RTEL1 regions are associated with development of glioma. While some of these germline variants are associated with all gliomas (e.g. rs2736100 in TERT), others are associated with a specific morphologic and/or molecular subtype. For example, the RTEL1 region variants are associated with primary glioblastoma and rs55705857 in CCDC26 is associated with 1p/19q co-deleted oligodendrogliomas and with IDH mutant astrocytic gliomas. We hypothesized that germline variants in these regions will be associated with other molecular subtypes. The Cancer Genome Atlas (TCGA) and other groups have described molecular subtypes of glioma based on acquired somatic mutation patterns. Herein, we grouped glioma patients into mutation-based molecular subgroups based on three molecular alterations and determined if germline polymorphisms are associated with these mutation-based molecular subtypes. Methods: Five molecular subtypes were defined based on combinations of the following molecular alterations: TERT promoter mutation (TERTmut vs. TERTwt), IDH1/2 mutation (IDH mut vs. IDH wt) and 1p/19q co-deletion (1p19qcodel vs. 1p19q noncodel). Germline single nucleotide polymorphisms (SNPs) were evaluated by custom Illumina array analysis of blood-derived DNA and 1K genome imputation. Results: One hundred ninety-nine gliomas (24 oligodendrogliomas, 59 mixed oligoastrocytomas, 41 grade 2-3 astrocytomas and 75 glioblastomas) had both SNP data and mutation data available in order to assign them into the five molecular subgroups. The prevalence of each of the molecular subtypes was as follows: TERTmut/IDHmut/1p19qcodel (20%), TERTmut/IDHmut/1p19qnoncodel (5%), TERTmut/IDHwt/1p19qnoncodel (32%), TERTwt/IDHmut/1p19qnondel (35%) and TERTwt/IDHwt/1p19qnoncodel (8%). The TERT SNP (rs2736100) was protective for TERTmut/IDHmut/1p19qnoncodel and TERTwt/IDHmut/1p19qnoncodel gliomas. The CCDC26 SNP (rs55705857) was strongly associated with the risk of developing TERTmut/IDHmut/1p19qcodel and TERTwt/IDHmut/1p19qnoncodel gliomas. The TP53 SNP (rs7837822) was strongly associated with risk of developing TERTmut/IDHmut/1p19qnoncodel and TERTwt/IDHmut/1p19qnoncodel gliomas. Interestingly, while one RTEL1 region SNP (rs6062297) was strongly associated with glioma risk, RTEL1 SNPs rs6010620 and rs2297440 were protective for the development of TERTmut/IDHwt/1p19qnoncodel gliomas. We are currently in the process of validating these results using the TCGA glioblastoma and low grade glioma data. Conclusions: Glioma patients can be meaningfully classified according to their acquired mutation subtype. Importantly, our results suggest that there are significant associations between germline polymorphisms and mutation-based glioma molecular subtypes. Citation Format: Jeanette E. Eckel-Passow, Thomas M. Kollmeyer, Gobinda Sarkar, Anisha Chada, Paul A. Decker, Matthew L. Kosel, Alissa A. Caron, Hugues Sicotte, Kannabiran Nandakumar, Naresh Prodduturi, Brian P. O'Neill, Daniel H. Lachance, Robert B. Jenkins. The association of glioma germline risk SNPs with mutation-based molecular subgroups. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4714. doi:10.1158/1538-7445.AM2014-4714
Abstract 4720: Evaluation of a genomic classifier (Decipher®) in subsets of primary tumors with common prostate cancer genomic alterations
Abstract Background ETS gene fusions and PTEN loss are the most common genomic alteration events in prostate cancer that stratify patients into molecularly distinct subtypes. Recently, a commercially available genomic classifier (GC, DecipherTM) has been validated to predict metastasis in patients with high-risk prostate cancer. In this study we evaluated the robustness of the GC model in the light of prostate cancer molecular heterogeneity. Methods: Analysis of PTEN expression loss, ERG overexpression and GC scores were performed on a previously reported genome-wide microarray dataset (Karnes et al., 2013). Microarray probesets mapping to exons of PTEN were benchmarked to identify a representative exon whose loss of expression was highly correlated to FISH analysis for PTEN deletion (PTEN-loss) performed on an independent dataset. ERG overexpression (ERG+) was determined similarly and the microarray probesets that best correlate with the FISH status (in independent dataset) were used to annotate the ERG status of the samples in this study. Receiver operating characteristic area under the curve (AUC), and multivariable regression analysis were used to assess GC performance for predicting metastasis in subsets of patient tumors with genomic alterations. Results Using the microarray method 42% of the tumors had ERG overexpression, 23% had PTEN-loss and 11% had both events. ERG+ and PTEN-loss were not on their own predictive of metastasis with AUCs of 0.52 (CI:0.44-0.6) and 0.47(CI 0.39-0.56), respectively. In ERG+ tumors GC had an AUC of 0.82 (p=4e-7) and high GC score ERG+ patients had a hazard ratio (HR) of 100 (p=6e-7) for metastasis. Similarly, in PTEN-loss tumors GC had an AUC of 0.83 (p=7.9e-5) and high GC score PTEN-loss patients had an HR of 62 (p=1.8e-4) for metastasis. When GC was evaluated in patient tumors with both ERG+ and PTEN-loss the AUC was 0.85 (p=2e-15) and high GC score patients had an HR of 95 (p=4e-4) for metastasis. In multivariable analysis, Decipher was the only significant risk factor with an HR of 55 (CI 12.2-249, p=1.8e-7) for metastasis after adjusting for ERG+, PTEN-loss, Gleason score, PSA, tumor stage, margins and adjuvant treatment. Conclusion The Decipher genomic classifier is a powerful prognostic marker that retains its significance for predicting metastasis in subsets of patients with tumors that harbor common genomic alterations. Patients with high GC scores and these alterations may represent an extremely high-risk subset of prostate cancer. Citation Format: Mohammed Alshalalfa, Ismael Vergara, Nicholas Erho, Elai Davicioni, Robert Jenkins, Kollmeyer Thomas. Evaluation of a genomic classifier (Decipher®) in subsets of primary tumors with common prostate cancer genomic alterations. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4720. doi:10.1158/1538-7445.AM2014-4720
Abstract 4207: The germline rs55705857 risk allele is not preferentially gained in gliomas with 8q24 duplication.
Abstract Background: Gliomas are primary malignant brain tumors with significant morbidity and mortality. Single nucleotide polymorphisms (SNPs) mapped to 8q24 have been shown to be associated with glioma development. Recently, we identified seven SNPs (through tag SNP genotyping/imputation, pooled next-generation sequencing using long-range PCR, and validation SNP genotyping) that are highly associated with the risk of developing glioma. After stratifying by histologic and tumor subtype, one SNP, rs55705857, in the 8q24.21 region near CCDC26 was significantly associated with oligodendroglial tumors and IDH mutated astrocytic gliomas with high odds ratios (ORs ∼6.0) (Jenkins et al. Nature Genet. 44:1122;2012). By array comparative genomic hybridization (aCGH), a significant proportion of oligodendroglial tumors and IDH mutated astrocytomas have been shown to duplicate 8q24 (Kitange et al., Genes Chr Cancer 42:68;2005; Nousmehr et al. Cancer Cell 17:510;2010). We were interested in learning if the germline risk allele of rs55705857 is associated with gliomas that duplicate 8q24. We were also interested in learning if the risk allele is preferentially gained in gliomas that duplicate 8q24. Methods: We performed aCGH on 217 tumor samples. rs55705857 germline genotype was available on 120 of the patients; of which 30 carried the risk (G) allele. In addition, we sequenced the rs55805857 region in 48 gliomas, 15 of which exhibited gain or duplication of chromosome 8, 8q, or 8q24. The ratio of the Sanger-sequencing peak heights at and around rs55705857 was used to determine which allele (risk or wild-type) was gained. Results: All 15 duplications included rs55705857 and the immediately adjacent regions. Of the 30 patients who carried the germline risk (G) allele for rs55707857, 8 (26.7%) exhibited duplication of 8q24 upon aCGH analysis of their glioma. Of the 90 patients who only carried the wild-type (A) allele, 7 (7.5%) exhibited duplications of 8q24 upon aCGH analysis of their glioma. This difference in proportion is statistically significant (p=0.024, Fischer exact test). Of the 15 tumors with duplication of 8q24, 8 came from patients who were germline rs55705857 heterozygotes (AG). Of these 8 germline heterozygotes with duplication of 8q24, 4 gained the risk (G) allele, 2 gained the wild-type (A) allele and 2 exhibited gain of both alleles in their tumor specimens. Conclusions: While the results require replication, our data suggest that carrying the risk allele for rs55705857 predisposes to the development of gliomas that subsequently duplicate 8q24. However, gliomas with duplication of 8q24 do not preferentially gain the risk rs55705857 allele. This result implies that, while the duplication always includes the rs55705857 region, the risk allele or region is not the direct target of the duplication. Citation Format: Amanda L. Rynearson, Kirsten A. Schowalter, Stephanie R. Fink, Thomas M. Kollmeyer, Chandralekha Halder, Gobinda Sarkar, Alissa A. Caron, Rachel A. Pauley, Daniel H. Lachance, Brian Patrick O'Neill, Robert B. Jenkins. The germline rs55705857 risk allele is not preferentially gained in gliomas with 8q24 duplication. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4207. doi:10.1158/1538-7445.AM2013-4207
Validation of a Genomic Classifier that Predicts Metastasis Following Radical Prostatectomy in an At Risk Patient Population
Genomewide association studies (GWAS) and candidate‐gene studies have implicated single‐nucleotide polymorphisms (SNPs) in at least 45 different genes as putative glioma risk factors. Attempts to validate these associations have yielded variable results and few genetic risk factors have been consistently replicated. We conducted a case‐control study of Caucasian glioma cases and controls from the University of California San Francisco (810 cases, 512 controls) and the Mayo Clinic (852 cases, 789 controls) in an attempt to replicate previously reported genetic risk factors for glioma. Sixty SNPs selected from the literature (eight from GWAS and 52 from candidate‐gene studies) were successfully genotyped on an Illumina custom genotyping panel. Eight SNPs in/near seven different genes (TERT, EGFR, CCDC26, CDKN2A, PHLDB1, RTEL1, TP53) were significantly associated with glioma risk in the combined dataset (P < 0.05), with all associations in the same direction as in previous reports. Several SNP associations showed considerable differences across histologic subtype. All eight successfully replicated associations were first identified by GWAS, although none of the putative risk SNPs from candidate‐gene studies was associated in the full case‐control sample (all P values > 0.05). Although several confirmed associations are located near genes long known to be involved in gliomagenesis (e.g., EGFR, CDKN2A, TP53), these associations were first discovered by the GWAS approach and are in noncoding regions. These results highlight that the deficiencies of the candidate‐gene approach lay in selecting both appropriate genes and relevant SNPs within these genes.
Sleeping Beauty
–Mediated Somatic Mutagenesis Implicates
CSF1
in the Formation of High-Grade Astrocytomas