EPID-12. USING GERMLINE VARIANTS TO PREDICT GLIOMA RISK AND IDENTIFY GLIOMA SUBTYPE PRE-OPERATIVELY. (5th November 2018)

• Record Type: Journal Article
• Authors: Eckel-Passow, Jeanette; Decker, Paul; Kosel, Matthew; Kollmeyer, Thomas; Molinaro, Annette; Rice, Terri; Caron, Alissa; Drucker, Kristen; Praska, Corinne; Pekmezci, Melike; Hansen, Helen; McCoy, Lucie; Bracci, Paige; Erickson, Bradley; Wiemels, Joseph; Wiencke, John; Bondy, Melissa; Melin, Beatrice; Burns, Terry; Giannini, Caterina; Lachance, Daniel; Wrensch, Margaret; Jenkins, Robert
• Is Part Of: Neuro-oncology. Volume 20(2018)Supplement 6
• Page Start: vi82
• Page End: vi82
• Publication Date: 2018-11-05
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noy148.339
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: To date, 25 single nucleotide polymorphisms (SNPs) have been shown to be associated with overall glioma risk or with risk of specific subtypes of glioma. We hypothesized that the inclusion of these 25 SNPs with patient age at diagnosis and sex could predict risk of glioma as well as predict IDH mutation status. Thus, case-control design and multinomial logistic regression were used to develop models to estimate the risk of glioma development while accounting for molecular subtypes. Case-case design and logistic regression were used to develop models to predict IDH mutation status. Each model included all 25 glioma risk SNPs, patient age at diagnosis and sex. A total of 1273 glioma cases and 443 controls from Mayo Clinic were used in the discovery set, and 852 glioma cases and 231 controls from UCSF were used in the validation set. All samples were genotyped using a custom Illumina OncoArray. We observed that patients in the highest 5% of the risk score had more than a 14-fold increased relative risk of developing an IDH-mutant glioma, compared to patients with median risk score. Large differences in lifetime absolute risk were observed at the extremes of the risk score percentile categories. For both IDH-mutated 1p/19q non-codeleted glioma and IDH-mutated 1p/19q-codeleted glioma, the lifetime risk increased from almost null to 2.3% and almost null to 1.7%, respectively. The SNP-based model that predicted IDH mutation status had a validation c-index of 0.85. These results suggest that germline genotyping has the potential to provide a new tool for clinicians for the initial management of newly-discovered brain lesions. Specifically, given the low lifetime risk of glioma, SNP-based risk scores should not be useful for general population screening. However, with further research these risk scores may be useful in certain clinically-defined high-risk groups.