Citations

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 Purpose: Mammographic breast density (MBD) is decreased by tamoxifen, but the effect of aromatase inhibitors is less clear. Experimental Design: We enrolled early-stage postmenopausal patients with breast cancer initiating adjuvant aromatase inhibitor therapy and ascertained mammograms before and at an average 10 months of aromatase inhibitor therapy. We matched cases to healthy postmenopausal women (controls) from a large mammography screening cohort on age, baseline body mass index, baseline MBD, and interval between mammograms. We estimated change in MBD using a computer-assisted thresholding program (Cumulus) and compared differences between cases and matched controls. Results: In predominantly White women (96%), we found 14% of the 387 eligible cases had a MBD reduction of at least 5% after an average of 10 months of aromatase inhibitor therapy. MBD reductions were associated with higher baseline MBD, aromatase inhibitor use for more than 12 months, and prior postmenopausal hormone use. Comparing each case with her matched control, there was no evidence of an association of change in MBD with aromatase inhibitor therapy [median case–control difference among 369 pairs was −0.1% (10th and 90th percentile: −5.9%, 5.2%) P = 0.51]. Case–control differences were similar by type of aromatase inhibitor (P's 0.41 and 0.56); prior use of postmenopausal hormones (P = 0.85); baseline MBD (P = 0.55); and length of aromatase inhibitor therapy (P = 0.08). Conclusions: In postmenopausal women treated with aromatase inhibitors, 14% of cases had a MBD reduction of more than 5%, but these decreases did not differ from matched controls. These data suggest that MBD is not a clinically useful biomarker for predicting the value of aromatase inhibitor therapy in White postmenopausal women. Clin Cancer Res; 19(8); 2144–53. ©2013 AACR.

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.