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Barnholtz-Sloan, Jill S

0000-0001-6190-9304

Mayo Clinic

Central Brain Tumor Registry of the United States, Hinsdale, Illinois.

Citations 27

Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma

Cancer Research | February 1, 2019 | Volume: 79 | Issue: 8 | Pages: 2065-2071

10.1158/0008-5472.can-18-2888 | PMID 30709929

Abstract Genome-wide association studies (GWAS) have so far identified 25 loci associated with glioma risk, with most showing specificity for either glioblastoma (GBM) or non-GBM tumors. The majority of these GWAS susceptibility variants reside in noncoding regions and the causal genes underlying the associations are largely unknown. Here we performed a transcriptome-wide association study to search for novel risk loci and candidate causal genes at known GWAS loci using Genotype-Tissue Expression Project (GTEx) data to predict cis-predicted gene expression in relation to GBM and non-GBM risk in conjunction with GWAS summary statistics on 12,488 glioma cases (6,183 GBM and 5,820 non-GBM) and 18,169 controls. Imposing a Bonferroni-corrected significance level of P < 5.69 × 10−6, we identified 31 genes, including GALNT6 at 12q13.33, as a candidate novel risk locus for GBM (mean Z = 4.43; P = 5.68 × 10−6). GALNT6 resides at least 55 Mb away from any previously identified glioma risk variant, while all other 30 significantly associated genes were located within 1 Mb of known GWAS-identified loci and were not significant after conditioning on the known GWAS-identified variants. These data identify a novel locus (GALNT6 at 12q13.33) and 30 genes at 12 known glioma risk loci associated with glioma risk, providing further insights into glioma tumorigenesis. Significance: This study identifies new genes associated with glioma risk, increasing understanding of how these tumors develop.
Sex differences in GBM revealed by analysis of patient imaging, transcriptome, and survival data

Science Translational Medicine | January 2, 2019 | Volume: 11 | Issue: 473 | Pages: No page available

10.1126/scitranslmed.aao5253 | PMID 30602536

Male and female glioblastomas are biologically distinct, and improving outcomes may require sex-specific approaches to treatment.
Aspirin, NSAIDs, and Glioma Risk: Original Data from the Glioma International Case–Control Study and a Meta-analysis

Cancer Epidemiology, Biomarkers & Prevention | November 27, 2018 | Volume: 28 | Issue: 3 | Pages: 555-562

10.1158/1055-9965.epi-18-0702 | PMID 30482874

Abstract Background: There have been few studies of sufficient size to address the relationship between glioma risk and the use of aspirin or NSAIDs, and results have been conflicting. The purpose of this study was to examine the associations between glioma and aspirin/NSAID use, and to aggregate these findings with prior published studies using meta-analysis. Methods: The Glioma International Case-Control Study (GICC) consists of 4,533 glioma cases and 4,171 controls recruited from 2010 to 2013. Interviews were conducted using a standardized questionnaire to obtain information on aspirin/NSAID use. We examined history of regular use for ≥6 months and duration-response. Restricted maximum likelihood meta-regression models were used to aggregate site-specific estimates, and to combine GICC estimates with previously published studies. Results: A history of daily aspirin use for ≥6 months was associated with a 38% lower glioma risk, compared with not having a history of daily use [adjusted meta-OR = 0.62; 95% confidence interval (CI), 0.54–0.70]. There was a significant duration-response trend (P = 1.67 × 10−17), with lower ORs for increasing duration of aspirin use. Duration-response trends were not observed for NSAID use. In the meta-analysis aggregating GICC data with five previous studies, there was a marginally significant association between use of aspirin and glioma (mOR = 0.84; 95% CI, 0.70–1.02), but no association for NSAID use. Conclusions: Our study suggests that aspirin may be associated with a reduced risk of glioma. Impact: These results imply that aspirin use may be associated with decreased glioma risk. Further research examining the association between aspirin use and glioma risk is warranted.
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

Identifying DNA methylation biomarkers for non-endoscopic detection of Barrett’s esophagus

Science Translational Medicine | January 17, 2018 | Volume: 10 | Issue: 424 | Pages: No page available

10.1126/scitranslmed.aao5848 | PMID 29343623

Combining DNA methylation markers with a swallowable device for sampling the distal esophagus effectively detects Barrett’s neoplasias.
RNA Sequencing Identifies Transcriptionally Viable Gene Fusions in Esophageal Adenocarcinomas

Cancer Research | August 8, 2016 | Volume: 76 | Issue: 19 | Pages: 5628-5633

10.1158/0008-5472.can-16-0979 | PMID 27503924

Abstract Esophageal adenocarcinoma is a deadly cancer with increasing incidence in the United States, but mechanisms underlying pathogenesis are still mostly elusive. In addressing this question, we assessed gene fusion landscapes by comprehensive RNA sequencing (RNAseq) of 55 pretreatment esophageal adenocarcinoma and 49 nonmalignant biopsy tissues from patients undergoing endoscopy for Barrett's esophagus. In this cohort, we identified 21 novel candidate esophageal adenocarcinoma–associated fusions occurring in 3.33% to 11.67% of esophageal adenocarcinomas. Two candidate fusions were selected for validation by PCR and Sanger sequencing in an independent set of pretreatment esophageal adenocarcinoma (N = 115) and nonmalignant (N = 183) biopsy tissues. In particular, we observed RPS6KB1–VMP1 gene fusion as a recurrent event occurring in approximately 10% of esophageal adenocarcinoma cases. Notably, esophageal adenocarcinoma cases harboring RPS6KB1–VMP1 fusions exhibited significantly poorer overall survival as compared with fusion-negative cases. Mechanistic investigations established that the RPS6KB1–VMP1 transcript coded for a fusion protein, which significantly enhanced the growth rate of nondysplastic Barrett's esophagus cells. Compared with the wild-type VMP1 protein, which mediates normal cellular autophagy, RPS6KB1–VMP1 fusion exhibited aberrant subcellular localization and was relatively ineffective in triggering autophagy. Overall, our findings identified RPS6KB1–VMP1 as a genetic fusion that promotes esophageal adenocarcinoma by modulating autophagy-related processes, offering new insights into the molecular pathogenesis of esophageal adenocarcinomas. Cancer Res; 76(19); 5628–33. ©2016 AACR.
Linkage and related analyses of Barrett's esophagus and its associated adenocarcinomas

Molecular Genetics & Genomic Medicine | March 19, 2016 | Volume: 4 | Issue: 4 | Pages: 407-419

10.1002/mgg3.211 | PMID 27468417

AbstractBackgroundFamilial aggregation and segregation analysis studies have provided evidence of a genetic basis for esophageal adenocarcinoma (EAC) and its premalignant precursor, Barrett's esophagus (BE). We aim to demonstrate the utility of linkage analysis to identify the genomic regions that might contain the genetic variants that predispose individuals to this complex trait (BE and EAC).MethodsWe genotyped 144 individuals in 42 multiplex pedigrees chosen from 1000 singly ascertained BE/EAC pedigrees, and performed both model‐based and model‐free linkage analyses, using S.A.G.E. and other software. Segregation models were fitted, from the data on both the 42 pedigrees and the 1000 pedigrees, to determine parameters for performing model‐based linkage analysis. Model‐based and model‐free linkage analyses were conducted in two sets of pedigrees: the 42 pedigrees and a subset of 18 pedigrees with female affected members that are expected to be more genetically homogeneous. Genome‐wide associations were also tested in these families.ResultsLinkage analyses on the 42 pedigrees identified several regions consistently suggestive of linkage by different linkage analysis methods on chromosomes 2q31, 12q23, and 4p14. A linkage on 15q26 is the only consistent linkage region identified in the 18 female‐affected pedigrees, in which the linkage signal is higher than in the 42 pedigrees. Other tentative linkage signals are also reported.ConclusionOur linkage study of BE/EAC pedigrees identified linkage regions on chromosomes 2, 4, 12, and 15, with some reported associations located within our linkage peaks. Our linkage results can help prioritize association tests to delineate the genetic determinants underlying susceptibility to BE and EAC.
History of chickenpox in glioma risk: a report from the glioma international case–control study (GICC)

Cancer Medicine | March 14, 2016 | Volume: 5 | Issue: 6 | Pages: 1352-1358

10.1002/cam4.682 | PMID 26972449

AbstractVaricella zoster virus (VZV) is a neurotropic α‐herpesvirus that causes chickenpox and establishes life‐long latency in the cranial nerve and dorsal root ganglia of the host. To date, VZV is the only virus consistently reported to have an inverse association with glioma. The Glioma International Case‐Control Study (GICC) is a large, multisite consortium with data on 4533 cases and 4171 controls collected across five countries. Here, we utilized the GICC data to confirm the previously reported associations between history of chickenpox and glioma risk in one of the largest studies to date on this topic. Using two‐stage random‐effects restricted maximum likelihood modeling, we found that a positive history of chickenpox was associated with a 21% lower glioma risk, adjusting for age and sex (95% confidence intervals (CI): 0.65–0.96). Furthermore, the protective effect of chickenpox was stronger for high‐grade gliomas. Our study provides additional evidence that the observed protective effect of chickenpox against glioma is unlikely to be coincidental. Future studies, including meta‐analyses of the literature and investigations of the potential biological mechanism, are warranted.
Predicting Barrett's Esophagus in Families: An Esophagus Translational Research Network (BETRNet) Model Fitting Clinical Data to a Familial Paradigm

Cancer Epidemiology, Biomarkers & Prevention | February 29, 2016 | Volume: 25 | Issue: 5 | Pages: 727-735

10.1158/1055-9965.epi-15-0832 | PMID 26929243

Abstract Background: Barrett's esophagus is often asymptomatic and only a small portion of Barrett's esophagus patients are currently diagnosed and under surveillance. Therefore, it is important to develop risk prediction models to identify high-risk individuals with Barrett's esophagus. Familial aggregation of Barrett's esophagus and esophageal adenocarcinoma, and the increased risk of esophageal adenocarcinoma for individuals with a family history, raise the necessity of including genetic factors in the prediction model. Methods to determine risk prediction models using both risk covariates and ascertained family data are not well developed. Methods: We developed a Barrett's Esophagus Translational Research Network (BETRNet) risk prediction model from 787 singly ascertained Barrett's esophagus pedigrees and 92 multiplex Barrett's esophagus pedigrees, fitting a multivariate logistic model that incorporates family history and clinical risk factors. The eight risk factors, age, sex, education level, parental status, smoking, heartburn frequency, regurgitation frequency, and use of acid suppressant, were included in the model. The prediction accuracy was evaluated on the training dataset and an independent validation dataset of 643 multiplex Barrett's esophagus pedigrees. Results: Our results indicate family information helps to predict Barrett's esophagus risk, and predicting in families improves both prediction calibration and discrimination accuracy. Conclusions: Our model can predict Barrett's esophagus risk for anyone with family members known to have, or not have, had Barrett's esophagus. It can predict risk for unrelated individuals without knowing any relatives' information. Impact: Our prediction model will shed light on effectively identifying high-risk individuals for Barrett's esophagus screening and surveillance, consequently allowing intervention at an early stage, and reducing mortality from esophageal adenocarcinoma. Cancer Epidemiol Biomarkers Prev; 25(5); 727–35. ©2016 AACR.