Johansen, Christoffer

AbstractBackgroundBladder cancer (BC) patients with advanced disease have poor outcomes. The use of patient‐reported outcomes (PROs) could lead to improvements in symptom management and hence quality of life (QoL). The aim of this study is to report correlations between selected PROs and QoL and thus to present symptoms that influence QoL. Identification of these symptoms during treatment can lead to earlier symptom management and thus secure improvements in QoL.MethodsBC patients in chemo‐ or immunotherapy for locally advanced or metastatic disease reported weekly PROs for the duration of their treatment. The PROs included EORTC QLQ‐C30 and QLQ‐BLM30 and 45 selected PRO‐CTCAE items. Spearman's correlation analysis was performed for all PRO‐CTCAE items and QLQ‐C30 global QoL and subdomains.ResultsIn this study, 78 BC patients reported 724 questionnaires. Spearman's analysis showed significant correlations between almost all PRO‐CTCAE items and the expected domain of QoL. The PRO‐CTCAE items with the strongest correlations with QoL were anxiety (F, frequency item) and emotional function (rs = −0.603, P < .0001), concentration (S, severity item) and cognitive function (rs = −0.704, P < .0001), discouraged (F) and emotional function (rs = −0.659, P < .0001), fatigue (S) and role function (rs = −0.659, P < .0001) and sad (F) and emotional function (rs = −0.711, P < .0001). The weakest correlations were found for the PRO‐CTCAE items urinary frequency, incontinence and urge, all with variations in the direction and significance of the correlations.ConclusionsThis study delivers information on which PROs may influence QoL for patients in clinical trials or daily clinic. Psychological issues have a strong impact on QoL and should be dealt with during treatment to secure the best possible QoL for BC patients.

Abstract Background The etiological basis of glioma is poorly understood. We have used genetic markers in a Mendelian Randomisation (MR) framework to examine if lifestyle, cardiometabolic and inflammatory factors influence the risk of glioma. This methodology reduces bias from confounding and is not affected by reverse causation. Methods We identified genetic instruments for 37 potentially modifiable risk factors and evaluated their association with glioma risk using data from a genome-wide association study of 12,488 glioma patients and 18,169 controls. We used the estimated odds ratio of glioma associated with each of the genetically defined traits to infer evidence for a causal relationship with the following exposures: lifestyle and dietary factors (height, plasma IGF-1, blood carnitine, blood methionine, blood selenium, blood zinc, circulating adiponectin, circulating carotenoids, iron status, serum calcium, vitamin [A1, B12, B6, E and 25-hydroxyvitamin D], fatty acids levels [mono-unsaturated, omega-3 and omega-6] and circulating fetuin-A); cardiometabolic factors (birth weight, HDL cholesterol, LDL cholesterol, total cholesterol, total triglycerides, basal metabolic rate, body fat percentage, body mass index, fasting glucose, fasting proinsulin, HbA1C levels, diastolic and systolic blood pressure, waist circumference, waist-to-hip ratio) were included; inflammatory factors (C-reactive protein (CRP), plasma IL-6 sRa and serum IgE). Results After correction for the testing of multiple potential risk factors and excluding associations driven by one single nucleotide polymorphism (SNP) no significant association with glioma risk was observed (i.e. PCorrected > 0.05). Conclusions This study did not provide evidence supporting any of the 37 factors examined as having a significant influence on glioma risk.

Abstract BACKGROUND: Approximately 5% of gliomas occur in individuals with a family history of glioma, and first-degree relatives of brain tumor cases have a two-fold increase in risk of brain tumor. Recent somatic characterization has shown that tumors from familial cases are indistinguishable from sporadic cases, suggesting that familial cases may arise through similar mechanisms of gliomagenesis, and therefore may be associated with common variants as well as rare mutations. In this analysis, we assessed whether previously identified common risk variants are associated with familial glioma. METHODS: Data were obtained from the Glioma International Case Control (GICC) and Gliogene studies for 448 cases with reported family history, 4,405 cases without reported family history, and 3,288 controls. We assessed 25 risk loci previously identified by glioma GWAS, and odds ratios (OR) and 95% confidence intervals (95%CI) were calculated using an additive genetic logistic regression model adjusted for age, sex, and the first two principal components for familial cases versus unaffected controls, and non-familial cases versus controls. Results were considered significant at p&lt;0.002 (Bonferroni correction for 25 tests). RESULTS: Significant associations were detected at 5/25 loci, including TERT, EGFR, CCDC26, CDKN2B, and RTEL1. The strongest association was at rs55705857 (CCDC26, OR=2.7, p=7.49x10-17). For GBM (222 familial cases), significant associations were detected at 6/26 loci (TERT, EGFR, CDKN2B, TP53 and RTEL1), while in non-GBM (205 familial cases) significant associations were detected at 3/25 loci (LRIG1, CCDC26, PHLDB1). These SNPs were further examined using a case-only approach comparing familial to non-familial cases, and there was no significant difference in allele frequencies by family history status. There was a strong correlation between log(OR) for familial cases only versus non-familial cases (adjusted R2=0.88). CONCLUSIONS: In this analysis we identified a significant association between familial glioma and five common risk loci previously identified by glioma GWAS. This provides further evidence of shared pathways of genetic risk and gliomagenesis between familial and non-familial glioma. Further exploration is necessary to determine the overall contribution of common genetic variation to risk of familial glioma. Citation Format: Quinn T. Ostrom, Georgina Armstrong, Christopher I. Amos, Jonine L. Bernstein, Elizabeth B. Claus, Jeanette E. Eckel-Passow, Dora Il'yasova, Christoffer Johansen, Daniel H. Lachance, Rose K. Lai, Ryan T. Merrell, Sara H. Olson, Joellen H. Schildkraut, Sanjay S. Shete, Richard S. Houlston, Robert B. Jenkins, Margaret R. Wrensch, Beatrice Melin, Jill S. Barnholtz-Sloan, Melissa L. Bondy. Previously identified common glioma risk SNPs are associated with familial glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4173.

Glioma incidence is highest in non‐Hispanic Whites, and to date, glioma genome‐wide association studies (GWAS) to date have only included European ancestry (EA) populations. African Americans and Hispanics in the US have varying proportions of EA, African (AA) and Native American ancestries (NAA). It is unknown if identified GWAS loci or increased EA is associated with increased glioma risk. We assessed whether EA was associated with glioma in African Americans and Hispanics. Data were obtained for 832 cases and 675 controls from the Glioma International Case–Control Study and GliomaSE Case–Control Study previously estimated to have <80% EA, or self‐identify as non‐White. We estimated global and local ancestry using fastStructure and RFMix, respectively, using 1,000 genomes project reference populations. Within groups with ≥40% AA (AFR ≥0.4 ), and ≥15% NAA (AMR ≥0.15 ), genome‐wide association between local EA and glioma was evaluated using logistic regression conditioned on global EA for all gliomas. We identified two regions (7q21.11, p = 6.36 × 10 −4 ; 11p11.12, p = 7.0 × 10 −4 ) associated with increased EA, and one associated with decreased EA (20p12.13, p = 0.0026) in AFR ≥0.4 . In addition, we identified a peak at rs1620291 ( p = 4.36 × 10 −6 ) in 7q21.3. Among AMR ≥0.15 , we found an association between increased EA in one region (12q24.21, p = 8.38 × 10 −4 ), and decreased EA in two regions (8q24.21, p = 0. 0010; 20q13.33, p = 6.36 × 10 −4 ). No other significant associations were identified. This analysis identified an association between glioma and two regions previously identified in EA populations (8q24.21, 20q13.33) and four novel regions (7q21.11, 11p11.12, 12q24.21 and 20p12.13). The identifications of novel association with EA suggest regions to target for future genetic association studies.

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 &lt; 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.

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.

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.’

Abstract Glioma incidence is highest in non-Hispanic Whites, where it occurs ~2x as frequently compared with other race/ethnicity groups. Glioma GWAS to date have included European ancestry populations only, and it is unknown whether variants identified by these analyses are associated with glioma in non- European ancestry populations. African Americans and Hispanics are admixed populations with varying proportions of European ancestry. While global ancestry may be similar within admixed groups, the proportion of European ancestry at each allele can vary across the genome. As glioma is more common in European ancestry populations, the presence of increased local European ancestry in these admixed populations could be used to identify glioma risk loci. Here we assessed whether excess European ancestry at established risk loci (Melin et al, Nature Genetics, 2017) was associated with glioma risk in non-European ancestry populations. Global ancestry was estimated using fastStructure, and local ancestry was estimated using RFMix. Both methods used 1,000 genomes project reference populations (African: YRI; European: CEU; East Asian: CHB/JPT; and Native American: CLM/PEL/MXL). We evaluated differences in local European ancestry between cases and controls using logistic regression conditioned on global European ancestry within 500kb of 25 previously identified risk variants among individuals with ≥50% African ancestry, and ≥30% Native American ancestry for all gliomas, and for grade IV glioblastoma (GBM) and grade II-III non-GBM. There were 347 individuals (184 cases and 163 controls) with ≥50% global African ancestry, and 277 individuals (153 cases and 124 controls) with ≥30% global American ancestry. There was no significant difference in proportion of global European ancestry between cases and controls with ≥50% global African ancestry (cases: 18.2%, controls: 17.7%, p=0.6834), and no significant difference in proportion of global European ancestry between cases and controls with ≥30% global American ancestry (cases: 51.1%, controls: 49.0%, p=0.2123). Among individuals with &gt;50% African ancestry, we observed a nominally significant association between all glioma and increased local European ancestry at 7p11.2 (EGFR, pmin=0.0070) and between GBM and increased local European ancestry at 22q13.1 (CSNK1E, pmin=0.0098), both near SNPs previously associated with glioblastoma in majority European-ancestry populations. The dataset used for this analysis represents the largest collection of genotyped non-European glioma cases. These results suggest that glioma risk in African Americans may be associated with an increased local European ancestry variants at glioma risk loci previously identified in majority European ancestry populations (7p11.2 and 22q13.1). Citation Format: Quinn T. Ostrom, Kathleen M. Egan, L. Burt Nabors, Travis Gerke, Reid C. Thompson, Jeffrey J. Olson, Renato LaRocca, Sajeel Chowdhary, Jeanette E. Eckel-Passow, Georgina Armstrong, John K. Wiencke, Christopher I. Amos, Jonine L. Bernstein, Elizabeth B. Claus, Dora Il'yasova, Christoffer Johansen, Daniel H. Lachance, Rose Lai, Ryan T. Merrell, Sara H. Olson, Siegal Sadetzki, Joellen Schildkraut, Sanjay Shete, Richard S. Houlston, Robert B. Jenkins, Beatrice Melin, Melissa L. Bondy, Jill S. Barnholtz-Sloan. Evaluating glioma risk associated with extent of European admixture in African-Americans and Latinos [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 233.