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Rubin, Joshua B

0000-0002-7395-1937

A5053768944 | I1324021844

Mayo Clinic

St. Louis Children's Hospital

Citations 26

NIMG-16. IMPACT OF SEX DIFFERENCES AND TUMOR LOCATION ON SURVIVAL OUTCOMES IN GLIOBLASTOMA PATIENTS

Neuro-Oncology | November 5, 2018 | Volume: 20 | Issue: suppl_6 | Pages: vi179-vi179

10.1093/neuonc/noy148.743

NIMG-07. DEEP LEARNING DETECTS DIFFERENCES IN THE MRIs OF MALE AND FEMALE GLIOMAS

Neuro-Oncology | November 5, 2018 | Volume: 20 | Issue: suppl_6 | Pages: vi177-vi177

10.1093/neuonc/noy148.735

NIMG-12. RADIOGENOMICS ON VENUS AND MARS: IMPACT OF SEX-DIFFERENCES ON MRI AND GENETIC CORRELATIONS IN GLIOBLASTOMA

Neuro-Oncology | November 5, 2018 | Volume: 20 | Issue: suppl_6 | Pages: vi178-vi178

10.1093/neuonc/noy148.739

NIMG-19. SEX-SPECIFIC BRAIN MAPS FOR RISK OF SEIZURE AMONG GLIOMA PATIENTS

Neuro-Oncology | November 5, 2018 | Volume: 20 | Issue: suppl_6 | Pages: vi179-vi180

10.1093/neuonc/noy148.745

Age‐specific genome‐wide association study in glioblastoma identifies increased proportion of ‘lower grade glioma’‐like features associated with younger age

International Journal of Cancer | August 29, 2018 | Volume: 143 | Issue: 10 | Pages: 2359-2366

10.1002/ijc.31759 | PMID 30152087

Glioblastoma (GBM) is the most common malignant brain tumor in the United States. Incidence of GBM increases with age, and younger age‐at‐diagnosis is significantly associated with improved prognosis. While the relationship between candidate GBM risk SNPs and age‐at‐diagnosis has been explored, genome‐wide association studies (GWAS) have not previously been stratified by age. Potential age‐specific genetic effects were assessed in autosomal SNPs for GBM patients using data from four previous GWAS. Using age distribution tertiles (18–53, 54–64, 65+) datasets were analyzed using age‐stratified logistic regression to generate p values, odds ratios (OR), and 95% confidence intervals (95%CI), and then combined using meta‐analysis. There were 4,512 total GBM cases, and 10,582 controls used for analysis. Significant associations were detected at two previously identified SNPs in 7p11.2 (rs723527 [p54–63 = 1.50x10−9, OR54–63 = 1.28, 95%CI54–63 = 1.18–1.39; p64+ = 2.14x10−11, OR64+ = 1.32, 95%CI64+ = 1.21–1.43] and rs11979158 [p54–63 = 6.13x10−8, OR54–63 = 1.35, 95%CI54–63 = 1.21–1.50; p64+ = 2.18x10−10, OR64+ = 1.42, 95%CI64+ = 1.27–1.58]) but only in persons >54. There was also a significant association at the previously identified lower grade glioma (LGG) risk locus at 8q24.21 (rs55705857) in persons ages 18–53 (p18–53 = 9.30 × 10−11, OR18–53 = 1.76, 95%CI18–53 = 1.49–2.10). Within The Cancer Genome Atlas (TCGA) there was higher prevalence of ‘LGG’‐like tumor characteristics in GBM samples in those 18–53, with IDH1/2 mutation frequency of 15%, as compared to 2.1% [54–63] and 0.8% [64+] (p = 0.0005). Age‐specific differences in cancer susceptibility can provide important clues to etiology. The association of a SNP known to confer risk for IDH1/2 mutant glioma and higher prevalence of IDH1/2 mutation within younger individuals 18–53 suggests that more younger individuals may present initially with ‘secondary glioblastoma.’
Sex-specific gene and pathway modeling of inherited glioma risk

Neuro-Oncology | August 8, 2018 | Volume: 21 | Issue: 1 | Pages: 71-82

10.1093/neuonc/noy135 | PMID 30124908