Abstract 3023: Identifying colorectal cancer biomarkers using a targeted proteomics platform with extensive coverage

Despite advances in treatment, colorectal cancer remains one of the leading causes of cancer-specific death. To decrease colorectal cancer mortality, better and more cost-efficient tools for risk prediction and early detection are needed. One area that has shown promise is using protein biomarkers, measured in blood, to detect individuals with early-stage disease or at increased risk. The primary aim of this study was therefore to identify novel protein biomarkers associated with colorectal cancer risk and the secondary aim was to validate protein biomarkers that had been described in previous studies. We included data and samples from 185 incident colorectal cancer cases and 185 controls (matched on age, sex, sampling date, and the number of freeze-thaw cycles) from the Northern Sweden Health and Disease Study (NSHDS). Samples were collected between six years and three months prior to the diagnosis date of each case and concentrations of 1536 individual proteins were measured in plasma samples using the Olink Explore 1536 platform (Olink Proteomics). Prior to statistical analyses, 249 proteins were excluded, either due to not passing quality control or having more than 50% of the concentrations below the limit of detection. In addition, we also excluded extreme outliers. Conditional logistic regression was used to estimate Odds Ratios (ORs) and 95% confidence intervals (95% CI) for the association between protein concentrations and colorectal cancer risk. Multivariable models were adjusted for predetermined colorectal cancer risk factors, including body mass index, alcohol consumption, physical activity, smoking status, and level of education. When considering p<0.005 as a cut-off, we identified 20 proteins that were associated with colorectal cancer risk. Our top hit was TFF3 (Trefoil Factor 3) which was positively associated with colorectal cancer at a high significance level (multivariable OR per SD: 1.84 95% CI: 1.38 - 2.45). TFF3 was significant in men (FDR<0.1), but not in women (pheterogeneity <0.05). In addition, several of the top 20 proteins such as AREG, MMP7, and CXCL16 have been linked to the diagnosis or prognosis of colorectal cancer in earlier studies. To conclude, we identified one novel protein biomarker, TFF3, strongly associated with colorectal cancer risk and validated several proteins previously linked to the diagnosis or prognosis of colorectal cancer.

Citation Format: Justin Harbs, Matilda Rentoft, Xijia Liu, Beatrice S. Melin, Sophia Harlid, Bethany Van Guelpen. Identifying colorectal cancer biomarkers using a targeted proteomics platform with extensive coverage [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3023.

Lack of association between modifiable exposures and glioma risk: a Mendelian randomization analysis

Background

The etiological basis of glioma is poorly understood. We have used genetic markers in a Mendelian randomization (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 insulin-like growth factor 1, blood carnitine, blood methionine, blood selenium, blood zinc, circulating adiponectin, circulating carotenoids, iron status, serum calcium, vitamins (A1, B12, B6, E, and 25-hydroxyvitamin D), fatty acid levels (monounsaturated, omega-3, and omega-6) and circulating fetuin-A;

Cardiometabolic factors—birth weight, high density lipoprotein cholesterol, low density lipoprotein cholesterol, total cholesterol, total triglycerides, basal metabolic rate, body fat percentage, body mass index, fasting glucose, fasting proinsulin, glycated hemoglobin levels, diastolic and systolic blood pressure, waist circumference, waist-to-hip ratio; and

Inflammatory factors— C-reactive protein, plasma interleukin-6 receptor subunit alpha and serum immunoglobulin E.

Results

After correction for the testing of multiple potential risk factors and excluding associations driven by one single nucleotide polymorphism, no significant association with glioma risk was observed (ie, P_Corrected > 0.05).

Conclusions

This study did not provide evidence supporting any of the 37 factors examined as having a significant influence on glioma risk.

A whole-genome sequenced control population in northern Sweden reveals subregional genetic differences

The number of national reference populations that are whole-genome sequenced are rapidly increasing. Partly driving this development is the fact that genetic disease studies benefit from knowing the genetic variation typical for the geographical area of interest. A whole-genome sequenced Swedish national reference population (n = 1000) has been recently published but with few samples from northern Sweden. In the present study we have whole-genome sequenced a control population (n = 300) (ACpop) from Västerbotten County, a sparsely populated region in northern Sweden previously shown to be genetically different from southern Sweden. The aggregated variant frequencies within ACpop are publicly available (DOI 10.17044/NBIS/G000005) to function as a basic resource in clinical genetics and for genetic studies. Our analysis of ACpop, representing approximately 0.11% of the population in Västerbotten, indicates the presence of a genetic substructure within the county. Furthermore, a demographic analysis showed that the population from which samples were drawn was to a large extent geographically stationary, a finding that was corroborated in the genetic analysis down to the level of municipalities. Including ACpop in the reference population when imputing unknown variants in a Västerbotten cohort resulted in a strong increase in the number of high-confidence imputed variants (up to 81% for variants with minor allele frequency < 5%). ACpop was initially designed for cancer disease studies, but the genetic structure within the cohort will be of general interest for all genetic disease studies in northern Sweden.

Abstract 1194: Cross-cancer GWAS meta-analysis of more than 370,000 cases and 530,000 controls identifies multiple novel cancer risk regions

Genome-wide association studies (GWAS) have identified hundreds of common, low-penetrance alleles associated with cancer risk. However, known rare and common risk alleles only explain between 10% and 30% of the familial relative risk for different cancers and multiple lines of evidence indicate that many more risk alleles remain to be discovered. We have demonstrated genetic correlations between cancers, reflecting a shared genetic origin for solid tumors. These results suggest that jointly analyzing multiple cancer sites will lead to the discovery of novel risk regions.

We conducted a cross-cancer GWAS meta-analysis by leveraging GWAS summary statistics from 12 solid cancers (breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate and renal cancers) with a total of 373,818 cases and 532,382 controls of European ancestry. All studies had been imputed to either 1,000 Genomes or the Haplotype Reference Consortium panel. We conducted four meta-analysis using (1) fixed-effect, (2) random-effect, (3) one-sided subset (ASSET) and (4) two-sided subset (ASSET) models. The subset analysis were conducted assuming either the same direction of effects across cancers (one-sided ASSET) or allowed for opposite direction of effects across cancers (two-sided ASSET). In all analyses, we used tetrachoric correlations to account for sample overlap across cancer sites. In total, we tested 10,223,013 variants for association. We considered regions with a p-value&lt;1.25 × 10−8 in at least one of the four meta-analysis approaches and located at least 500kb away from known cancer risk SNPs as novel.

We identified eight novel regions that reached genome-wide significance. Of those eight regions, two were identified from fixed-effects meta-analysis, three from random effects meta-analysis, one from the two-sided subset analysis, and two regions (15.q15.3 and 21q22.3) were identified at p&lt;1.25 × 10−8 in three of the meta-analysis approaches. Among novel findings is a deleterious missense variant located in RREB1 previously associated with type 2 diabetes, a deleterious missense variant located in DSTYK previously associated with waist-to-hip ratio and triglycerides, and an intergenic variant in linkage disequilibrium (LD) with variants in TMEM18, previously associated with body mass index. Other potential target genes among the newly discovered regions include TP53BP1 and PCNT, both previously implicated in carcinogenesis.

Citation Format: Sara Lindström, Siddhartha Kar, Lu Wang, Constance Turman, James MacDonald, Theo Bammler, BCAC, OCAC, PRACTICAL, Jeroen Huyghe, Stephanie Schmit, Tracy A. O'Mara, Deborah J. Thompson, Puya Gharahkhani, Stuart MacGregor, Paul Brennan, Richard S. Houlston, Beatrice S. Melin, Christopher I. Amos, James McKay, Mark M. Iles, Matthew H. Law, Alison Klein, Laufey Amundadottir, Bogdan Pasaniuc, Paul Pharoah, Rayjean J. Hung, Peter Kraft. Cross-cancer GWAS meta-analysis of more than 370,000 cases and 530,000 controls identifies multiple novel cancer risk regions [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1194.

Abstract 30: Cross-cancer cross-tissue transcriptome-wide association study (TWAS) of 11 cancers identifies 56 novel genes

Although cancer is a heterogeneous disease, there are shared hallmark mechanisms across multiple tumor types. Because of this, identifying genes associated with multiple cancer types has the potential to shed light on general oncogenic mechanisms. Conversely, integrating evidence for genetic association across multiple cancers could identify novel genes missed in single-cancer analyses. Transcriptome Wide Association Studies (TWAS) have been successful in identifying genes associated with individual cancers. TWAS test whether genetically-predicted tissue-specific gene expression levels are associated with cancer risk. Although cross-cancer genome-wide association studies (GWAS) analyses have been performed previously, no cross-cancer TWAS has been conducted to date. Here, we implement a pipeline to perform cross-cancer, cross-tissue TWAS analysis. We use newly-developed multi-trait TWAS test statistics to integrate the TWAS results for association between 11 separated cancers and predicted gene expression in each of 43 GTEx tissues; these include a "sum" test and a "variance components" test, analogous to fixed- and random-effects meta-analyses. We then integrated the results across different tissues using the Aggregated Cauchy Association Test (ACAT), a novel powerful and robust test for combining association results under general correlation patterns. A total of 403 genes were significantly associated with at least one cancer type using predicted gene expression for at least one tissue (p&lt;0.05/899,338, Bonferroni adjusted for the total number of gene-cancer-tissue combinations tested); 96 additional genes were identified when combining test results across cancers (p&lt;0.05/81,758, adjusting for the total number of gene-tissue combinations tested); and 35 additional genes when further combining test results across tissue (p&lt;0.05/12,001, adjusting for the number of genes tested). Among these significant genes, 70 were not near previously-published GWAS index variants (&gt;250 kb distant). 14 of the 70 novel genes were identified from the single cancer single tissue test; an additional 43 were identified with the cross-cancer test; and another 13 were identified when further combining the results across tissues. The newly identified genes include RBBP8, which regulates cell proliferation and modulates BRCA1-mediated DNA repair, and TP53BP1, which is involved in double-strand break repair. Other newly identified genes are involved in chromatin structure, tumorigenesis, apoptosis, transcriptional regulation, DNA repair, immune system, oxidative damage and cell cycle, proliferation, progression, shape, structure, and migration.

Citation Format: Helian Feng, Arunabha Majumdar, Bogdan Pasaniuc, Hongjie Chen, Sara Lindström, BCAC, OCAC, PRACTICAL, Jeroen Huyghe, Stephanie L. Schmit, Tracy A. O'Mara, Deborah J. Thompson, Stuart MacGregor, Paul Brennan, James McKay, Richard S. Houlston, Beatrice S. Melin, Christopher Amos, Anne E. Cus, Mark M. Iles, Siddhartha Kar, Paul Pharoah, Rayjean J. Hung, Peter Kraft. Cross-cancer cross-tissue transcriptome-wide association study (TWAS) of 11 cancers identifies 56 novel genes [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 30.

A geographically matched control population efficiently limits the number of candidate disease-causing variants in an unbiased whole-genome analysis

Whole-genome sequencing is a promising approach for human autosomal dominant disease studies. However, the vast number of genetic variants observed by this method constitutes a challenge when trying to identify the causal variants. This is often handled by restricting disease studies to the most damaging variants, e.g. those found in coding regions, and overlooking the remaining genetic variation. Such a biased approach explains in part why the genetic causes of many families with dominantly inherited diseases, in spite of being included in whole-genome sequencing studies, are left unsolved today. Here we explore the use of a geographically matched control population to minimize the number of candidate disease-causing variants without excluding variants based on assumptions on genomic position or functional predictions. To exemplify the benefit of the geographically matched control population we apply a typical disease variant filtering strategy in a family with an autosomal dominant form of colorectal cancer. With the use of the geographically matched control population we end up with 26 candidate variants genome wide. This is in contrast to the tens of thousands of candidates left when only making use of available public variant datasets. The effect of the local control population is dual, it (1) reduces the total number of candidate variants shared between affected individuals, and more importantly (2) increases the rate by which the number of candidate variants are reduced as additional affected family members are included in the filtering strategy. We demonstrate that the application of a geographically matched control population effectively limits the number of candidate disease-causing variants and may provide the means by which variants suitable for functional studies are identified genome wide.

The association between longer relative leukocyte telomere length and risk of glioma is independent of the potentially confounding factors allergy, BMI, and smoking

PURPOSE

Previous studies have suggested an association between relative leukocyte telomere length (rLTL) and glioma risk. This association may be influenced by several factors, including allergies, BMI, and smoking. Previous studies have shown that individuals with asthma and allergy have shortened relative telomere length, and decreased risk of glioma. Though, the details and the interplay between rLTL, asthma and allergies, and glioma molecular phenotype is largely unknown.

METHODS

rLTL was measured by qPCR in a Swedish population-based glioma case-control cohort (421 cases and 671 controls). rLTL was related to glioma risk and health parameters associated with asthma and allergy, as well as molecular events in glioma including IDH1 mutation, 1p/19q co-deletion, and EGFR amplification.

RESULTS

Longer rLTL was associated with increased risk of glioma (OR = 1.16; 95% CI 1.02-1.31). Similar to previous reports, there was an inverse association between allergy and glioma risk. Specific, allergy symptoms including watery eyes was most strongly associated with glioma risk. High body mass index (BMI) a year prior diagnosis was significantly protective against glioma in our population. Adjusting for allergy, asthma, BMI, and smoking did not markedly change the association between longer rLTL and glioma risk. rLTL among cases was not associated with IDH1 mutation, 1p/19q co-deletion, or EGFR amplification, after adjusting for age at diagnosis and sex.

CONCLUSIONS

In this Swedish glioma case-control cohort, we identified that long rLTL increases the risk of glioma, an association not confounded by allergy, BMI, or smoking. This highlights the complex interplay of the immune system, rLTL and cancer risk.

Molecular subtyping of tumors from patients with familial glioma

Background

Single-gene mutation syndromes account for some familial glioma (FG); however, they make up only a small fraction of glioma families. Gliomas can be classified into 3 major molecular subtypes based on isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion. We hypothesized that the prevalence of molecular subtypes might differ in familial versus sporadic gliomas and that tumors in the same family should have the same molecular subtype.

Methods

Participants in the FG study (Gliogene) provided samples for germline DNA analysis. Formalin-fixed, paraffin-embedded tumors were obtained from a subset of FG cases, and DNA was extracted. We analyzed tissue from 75 families, including 10 families containing a second affected family member. Copy number variation data were obtained using a first-generation Affymetrix molecular inversion probe (MIP) array.

Results

Samples from 62 of 75 (83%) FG cases could be classified into the 3 subtypes. The prevalence of the molecular subtypes was: 30 (48%) IDH-wildtype, 21 (34%) IDH-mutant non-codeleted, and 11 (19%) IDH-mutant and 1p/19q codeleted. This distribution of molecular subtypes was not statistically different from that of sporadic gliomas (P = 0.54). Of 10 paired FG samples, molecular subtypes were concordant for 7 (κ = 0.59): 3 IDH-mutant non-codeleted, 2 IDH-wildtype, and 2 IDH-mutant and 1p/19q codeleted gliomas.

Conclusions

Our data suggest that within individual families, patients develop gliomas of the same molecular subtype. However, we did not observe differences in the prevalence of the molecular subtypes in FG compared with sporadic gliomas. These observations provide further insight into the distribution of molecular subtypes in FG.

Glioma-related seizures in relation to histopathological subtypes: a report from the glioma international case-control study

BACKGROUND

The purpose of this study was to evaluate the distribution of glioma-related seizures and seizure control at the time of tumor diagnosis with respect to tumor histologic subtypes, tumor treatment and patient characteristics, and to compare seizure history preceding tumor diagnosis (or study enrollment) between glioma patients and healthy controls.

METHODS

The Glioma International Case Control study (GICC) risk factor questionnaire collected information on demographics, past medical/medication history, and occupational history. Cases from eight centers were also asked detailed questions on seizures in relation to glioma diagnosis; cases (n = 4533) and controls (n = 4171) were also asked about seizures less than 2 years from diagnosis and previous seizure history more than 2 years prior to tumor diagnosis, including childhood seizures.

RESULTS

Low-grade gliomas (LGGs), particularly oligodendrogliomas/oligoastrocytomas, had the highest proportion of glioma-related seizures. Patients with low-grade astrocytoma demonstrated the most medically refractory seizures. A total of 83% of patients were using only one antiepileptic drug (AED), which was levetiracetam in 71% of cases. Gross total resection was strongly associated with reduced seizure frequency (p < 0.009). No significant difference was found between glioma cases and controls in terms of seizure occurring more than 2 years before diagnosis or during childhood.

CONCLUSIONS

Our study showed that glioma-related seizures were most common in low-grade gliomas. Gross total resection was associated with lower seizure frequency. Additionally, having a history of childhood seizures is not a risk factor ***for developing glioma-related seizures or glioma.

Mendelian randomisation study of the relationship between vitamin D and risk of glioma

To examine for a causal relationship between vitamin D and glioma risk we performed an analysis of genetic variants associated with serum 25-hydroxyvitamin D (25(OH)D) levels using Mendelian randomisation (MR), an approach unaffected by biases from confounding. Two-sample MR was undertaken using genome-wide association study data. Single nucleotide polymorphisms (SNPs) associated with 25(OH)D levels were used as instrumental variables (IVs). We calculated MR estimates for the odds ratio (OR) for 25(OH)D levels with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighted (IVW) and maximum likelihood estimation (MLE) methods. A non-significant association between 25(OH)D levels and glioma risk was shown using both the IVW (OR = 1.21, 95% confidence interval [CI] = 0.90–1.62, P = 0.201) and MLE (OR = 1.20, 95% CI = 0.98–1.48, P = 0.083) methods. In an exploratory analysis of tumour subtype, an inverse relationship between 25(OH)D levels and glioblastoma (GBM) risk was identified using the MLE method (OR = 0.62, 95% CI = 0.43–0.89, P = 0.010), but not the IVW method (OR = 0.62, 95% CI = 0.37–1.04, P = 0.070). No statistically significant association was shown between 25(OH)D levels and non-GBM glioma. Our results do not provide evidence for a causal relationship between 25(OH)D levels and all forms of glioma risk. More evidence is required to explore the relationship between 25(OH)D levels and risk of GBM.

Abstract 1302: Genome-wide association study of glioma reveals specific differences in genetic susceptibility to glioblastoma and non-glioblastoma

BACKGROUND: Glioma accounts for ~27% of all primary brain tumors and is responsible for ~13,000 cancer-related deaths in the US each year. Glioma tumors can be broadly classified into glioblastoma (GBM) and lower-grade non-GBM. Typically gliomas have a poor prognosis irrespective of medical care, with the most common form, GBM, having a five-year survival rate of only 5%. While genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, individual studies have had limited power to identify risk loci.

METHODS: We performed the largest glioma GWAS to date, comprising a meta-analysis of six existing GWAS (6,405 cases, 14,100 controls) as well as new GWAS from the Glioma International Case Control Consortium (GICC; 4,572 cases and 3,286 controls) and University of California, San Francisco (UCSF)-Mayo (1,519 cases, 804 controls), totaling 12,496 cases (6,191 classified as GBM, 5,819 as non-GBM) and 18,190 controls.

RESULTS: We identified five new risk loci for GBM at 1p31.3 (rs12752552; near JAK1, P=2.04×10-9, odds ratio (OR)=1.22), 11q14.1 (rs11233250; P=9.95×10-10, OR=1.24), 16p13.3 (rs2562152; near MPG, P=1.93x10-8, OR=1.21), 16q12.1 (rs10852606; HEATR3, P=1.29×10-11, OR=1.18), 22q13.1 (rs2235573; P=1.76×10-10, OR=1.15) and eight for non-GBM at 1q32.1 (rs4252707; MDM4, P=3.34×10-9, OR=1.19), 1q44 (rs12076373; AKT3, P=2.63×10-10, OR=1.23), 2q33.3 (rs7572263; near IDH1, P=2.18×10-10, OR=1.20), 3p14.1 (rs11706832; LRIG1, P=7.66×10-9, OR=1.15), 10q24.33 (rs11598018; OBFC1, P=3.39×10-8, OR=1.14), 11q21 (rs7107785; P=3.87×10-10, OR=1.16), 14q12 (rs10131032; P=5.07x10-11, OR=1.33) and 16p13.3 (rs3751667; P=2.61×10-9, OR=1.18). Case-only analyses confirmed the specificity of 11q14.1, 16p13.3 and 22q13.1 associations for GBM and 1q44, 2q33.3, 3p14.1, 11q21 and 14q12 for non-GBM tumors. In the combined meta-analysis, among previously published glioma risk SNPs, those for all glioma at 17p13.1 (TP53), GBM at 5p15.33 (TERT), 7p11.2 (EGFR), 9p21.3 (CDKN2B-AS1) and 20q13.33 (RTEL1) and for non-GBM at 8q24.21 (CCDC26), 11q23.2, 11q23.3 (PHLDB1) and 15q24.2 (ETFA) showed even greater evidence for association. SNPs at 10q25.2 and 12q12.1 for non-GBM tumors retained genome-wide significance (i.e. P&lt;5.0x10-8). Associations at the previously reported loci for GBM at 3q26.2 (near TERC) and 12q23.33 (POLR3B) did not retain statistical significance.

CONCLUSIONS: Our findings substantiate genetic susceptibility to GBM and non-GBM glioma being highly distinct, consistent with their distinctive molecular profiles presumably resulting from different etiological pathways. Functional analyses should lead to further insights into the biological basis of the different glioma histologies. Such information can inform gene discovery initiatives and therefore have a measurable impact on the successful development of new therapeutic agents.

Citation Format: Ben Kinnersley, Beatrice S. Melin, Jill S. Barnholtz-Sloan, Margaret R. Wrensch, Christoffer Johansen, Dora Il’yasova, Quinn Ostrom, and members of GICC, Karim Labreche, Jeanette E. Eckel-Passow, Paul A. Decker, Marianne Labussière, Ahmed Idbaih, Khe Hoang-Xuan, Anna-Luisa Di Stefano, Karima Mokhtari, Jean-Yves Delattre, Pilar Galan, Konstantinos Gousias, Johannes Schramm, Minouk J. Schoemaker, Sarah J. Fleming, Stefan Herms, Stefanie Heilmann, Marcus M. Nöthen, Heinz-Erich Wichmann, Stefan Schreiber, Anthony Swerdlow, Mark Lathrop, Matthias Simon, Marc Sanson, Preetha Rajaraman, Stephen Chanock, Martha Linet, Zhaoming Wang, Meredith Yeager, Rose K. Lai, Elizabeth B. Claus, Sara H. Olson, Robert B. Jenkins, Richard S. Houlston, Melissa L. Bondy. Genome-wide association study of glioma reveals specific differences in genetic susceptibility to glioblastoma and non-glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1302. doi:10.1158/1538-7445.AM2017-1302

Genome-wide association study of glioma subtypes identifies specific differences in genetic susceptibility to glioblastoma and non-glioblastoma tumors

Genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, but individual studies have had limited power to identify risk loci. We performed a meta-analysis of existing GWAS and two new GWAS, which totaled 12,496 cases and 18,190 controls. We identified five new loci for glioblastoma (GBM) at 1p31.3 (rs12752552; P = 2.04 × 10-9, odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 × 10-10, OR = 1.24), 16p13.3 (rs2562152; P = 1.93 × 10-8, OR = 1.21), 16q12.1 (rs10852606; P = 1.29 × 10-11, OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 × 10-10, OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 × 10-9, OR = 1.19), 1q44 (rs12076373; P = 2.63 × 10-10, OR = 1.23), 2q33.3 (rs7572263; P = 2.18 × 10-10, OR = 1.20), 3p14.1 (rs11706832; P = 7.66 × 10-9, OR = 1.15), 10q24.33 (rs11598018; P = 3.39 × 10-8, OR = 1.14), 11q21 (rs7107785; P = 3.87 × 10-10, OR = 1.16), 14q12 (rs10131032; P = 5.07 × 10-11, OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 × 10-9, OR = 1.18). These data substantiate that genetic susceptibility to GBM and non-GBM tumors are highly distinct, which likely reflects different etiology.

Abstract 3446: Aspirin, non-steroidal anti-inflammatory drugs (NSAIDs) and the risk of glioma: Results from the Glioma International Case Control Study

Background: Numerous epidemiologic studies have examined the association between aspirin (ASA), non-steroid anti-inflammatory drugs (NSAIDs) and the development of glioma, but the results have been inconsistent. The goal of this study was to evaluate the relationship between the intake of these drugs and glioma risk in a large, international case-control study.

Methods: Between 2010 and 2015, the Glioma International Case-Control Study (GICC) recruited newly diagnosed glioma cases and matched controls in 14 different sites across five countries. Each subject was interviewed using a standardized questionnaire to obtain NSAIDs and ASA use. We examined the associations between ever use (at least &gt; 6 months), duration of drug use and glioma histology. Ever use data on 4533 glioma cases and 4171 controls was combined using maximum likelihood estimation/restricted maximum likelihood meta-analysis methods. Furthermore, based on a priori hypotheses, we performed subgroup analyses based on gender and glioma histological grades.

Results: Use of ASA for &gt; 6 months was associated with a 33% lower glioma risk compared to those who never took it (adjusted Meta-OR 0.67, 95% CI 0.54-0.83). Duration of intake showed a significant trend test (p &lt; 0.0001), with ORs became lower for increasing number of years of ASA use. In subgroup analyses, intake of ASA was significantly associated with glioma risk in both men and women (adjusted Meta-OR = 0.65, 95% CI 0.51-0.84 for men; adjusted Meta-OR = 0.74, 95% CI 0.58-0.93 for women). ASA intake was protective for grade IV glioma (glioblastoma) and grade II/III glioma (adjusted meta-OR 0.63, 95% CI 0.5-0.8 for glioblastoma; adjusted meta-OR 0.67, 95% CI 0.50 - 0.89 for grade II/III glioma). For NSAIDs intake, ever use &gt; 6 months was not associated with glioma risk (adjusted meta-OR 0.87, 95% CI 0.71-1.07). However, NSAIDs use was protective for women (adjusted meta-OR 0.72, 95% CI 0.55-0.93) in subgroup analyses but not for men (adjusted meta-OR 1.03; 95% CI 0.86-1.23). The interaction between gender, NSAIDs and glioma risk was significant (p-value 0.0076).. Sensitivity analyses excluding those who took ASA or NSAIDs within the past 12 months for headache, and the removal of proxy respondents did not change our results.

Conclusion: ASA was associated with a significant protective effect for glioma, but NSAIDs were only associated with reduced glioma risk in women. Given the possibility of recall bias in case-control studies of brain tumors, we may verify dosage and duration of drug intake in those countries with electronic pharmacy records within the GICC.

Citation Format: Rose K. Lai, Renke Zhou, E. Susan Amirian, Christoffer Johansen, Michael E. Scheurer, Georgina N. Armstrong, Ching C. Lau, Elizabeth B. Claus, Jill S. Barnholtz-Sloan, Dora Il’yasova, Joellen Schildkraut, Francis Ali-Osman, Siegal Sadetzki, Richard Houlston, Robert B. Jenkins, Daniel Lachance, Sara H. Olson, Jonine L. Bernstein, Ryan T. Merrell, Margaret R. Wrensch, Faith G. Davis, Sanjay Shete, Christopher I. Amos, Beatrice S. Melin, Melissa Bondy. Aspirin, non-steroidal anti-inflammatory drugs (NSAIDs) and the risk of glioma: Results from the Glioma International Case Control Study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3446.

Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases.

It is unclear how often genetic mosaicism of chromosome X arises. Here, the authors examine women with cancer and cancer-free controls and show that X chromosome mosaicism occurs more frequently than on autosomes, especially on the inactive X chromosome, but is not linked to non-haematologic cancer risk

History of chickenpox in glioma risk: a report from the glioma international case-control study (GICC)

Varicella 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.

Approaching a Scientific Consensus on the Association between Allergies and Glioma Risk: A Report from the Glioma International Case-Control Study

BACKGROUND

Several previous studies have found inverse associations between glioma susceptibility and a history of allergies or other atopic conditions. Some evidence indicates that respiratory allergies are likely to be particularly relevant with regard to glioma risk. Using data from the Glioma International Case-Control Study (GICC), we examined the effects of respiratory allergies and other atopic conditions on glioma risk.

METHODS

The GICC contains detailed information on history of atopic conditions for 4,533 cases and 4,171 controls, recruited from 14 study sites across five countries. Using two-stage random-effects restricted maximum likelihood modeling to calculate meta-analysis ORs, we examined the associations between glioma and allergy status, respiratory allergy status, asthma, and eczema.

RESULTS

Having a history of respiratory allergies was associated with an approximately 30% lower glioma risk, compared with not having respiratory allergies (mOR, 0.72; 95% confidence interval, 0.58-0.90). This association was similar when restricting to high-grade glioma cases. Asthma and eczema were also significantly protective against glioma.

CONCLUSION

A substantial amount of data on the inverse association between atopic conditions and glioma has accumulated, and findings from the GICC study further strengthen the existing evidence that the relationship between atopy and glioma is unlikely to be coincidental.

IMPACT

As the literature approaches a consensus on the impact of allergies in glioma risk, future research can begin to shift focus to what the underlying biologic mechanism behind this association may be, which could, in turn, yield new opportunities for immunotherapy or cancer prevention.

The Glioma International Case-Control Study: A Report From the Genetic Epidemiology of Glioma International Consortium

Decades of research have established only a few etiological factors for glioma, which is a rare and highly fatal brain cancer. Common methodological challenges among glioma studies include small sample sizes, heterogeneity of tumor subtypes, and retrospective exposure assessment. Here, we briefly describe the Glioma International Case-Control (GICC) Study (recruitment, 2010-2013), a study being conducted by the Genetic Epidemiology of Glioma International Consortium that integrates data from multiple data collection sites, uses a common protocol and questionnaire, and includes biospecimen collection. To our knowledge, the GICC Study is the largest glioma study to date that includes collection of blood samples, which will allow for genetic analysis and interrogation of gene-environment interactions.

Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for Thirteen Cancer Types

BACKGROUND

Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.

METHODS

Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.

RESULTS

GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.

CONCLUSION

Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.

Further Confirmation of Germline Glioma Risk Variant rs78378222 in TP53 and Its Implication in Tumor Tissues via Integrative Analysis of TCGA Data

We confirmed strong association of rs78378222:A>C (per allele odds ratio [OR] = 3.14; P = 6.48 × 10(-11) ), a germline rare single-nucleotide polymorphism (SNP) in TP53, via imputation of a genome-wide association study of glioma (1,856 cases and 4,955 controls). We subsequently performed integrative analyses on the Cancer Genome Atlas (TCGA) data for GBM (glioblastoma multiforme) and LUAD (lung adenocarcinoma). Based on SNP data, we imputed genotypes for rs78378222 and selected individuals carrying rare risk allele (C). Using RNA sequencing data, we observed aberrant transcripts with ∼3 kb longer than normal for those individuals. Using exome sequencing data, we further showed that loss of haplotype carrying common protective allele (A) occurred somatically in GBM but not in LUAD. Our bioinformatic analysis suggests rare risk allele (C) disrupts mRNA termination, and an allelic loss of a genomic region harboring common protective allele (A) occurs during tumor initiation or progression for glioma.

Characterization of large structural genetic mosaicism in human autosomes

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.

Targeted sequencing in chromosome 17q linkage region identifies familial glioma candidates in the Gliogene Consortium

Glioma is a rare, but highly fatal, cancer that accounts for the majority of malignant primary brain tumors. Inherited predisposition to glioma has been consistently observed within non-syndromic families. Our previous studies, which involved non-parametric and parametric linkage analyses, both yielded significant linkage peaks on chromosome 17q. Here, we use data from next generation and Sanger sequencing to identify familial glioma candidate genes and variants on chromosome 17q for further investigation. We applied a filtering schema to narrow the original list of 4830 annotated variants down to 21 very rare (<0.1% frequency), non-synonymous variants. Our findings implicate the MYO19 and KIF18B genes and rare variants in SPAG9 and RUNDC1 as candidates worthy of further investigation. Burden testing and functional studies are planned.

Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33

Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.

Germline mutations in shelterin complex genes are associated with familial glioma

Gliomas are the most common brain tumor, with several histological subtypes of various malignancy grade. The genetic contribution to familial glioma is not well understood. Using whole exome sequencing of 90 individuals from 55 families, we identified two families with mutations in POT1 (p.G95C, p.E450X), a member of the telomere shelterin complex, shared by both affected individuals in each family and predicted to impact DNA binding and TPP1 binding, respectively. Validation in a separate cohort of 264 individuals from 246 families identified an additional mutation in POT1 (p.D617Efs), also predicted to disrupt TPP1 binding. All families with POT1 mutations had affected members with oligodendroglioma, a specific subtype of glioma more sensitive to irradiation. These findings are important for understanding the origin of glioma and could have importance for the future diagnostics and treatment of glioma.

Germline rearrangements in families with strong family history of glioma and malignant melanoma, colon, and breast cancer

BACKGROUND

Although familial susceptibility to glioma is known, the genetic basis for this susceptibility remains unidentified in the majority of glioma-specific families. An alternative approach to identifying such genes is to examine cancer pedigrees, which include glioma as one of several cancer phenotypes, to determine whether common chromosomal modifications might account for the familial aggregation of glioma and other cancers.

METHODS

Germline rearrangements in 146 glioma families (from the Gliogene Consortium; http://www.gliogene.org/) were examined using multiplex ligation-dependent probe amplification. These families all had at least 2 verified glioma cases and a third reported or verified glioma case in the same family or 2 glioma cases in the family with at least one family member affected with melanoma, colon, or breast cancer.The genomic areas covering TP53, CDKN2A, MLH1, and MSH2 were selected because these genes have been previously reported to be associated with cancer pedigrees known to include glioma.

RESULTS

We detected a single structural rearrangement, a deletion of exons 1-6 in MSH2, in the proband of one family with 3 cases with glioma and one relative with colon cancer.

CONCLUSIONS

Large deletions and duplications are rare events in familial glioma cases, even in families with a strong family history of cancers that may be involved in known cancer syndromes.

Loss of LRIG1 locus increases risk of early and late relapse of stage I/II breast cancer

Gains and losses at chromosome 3p12-21 are common in breast tumors and associated with patient outcomes. We hypothesized that the LRIG1 gene at 3p14.1, whose product functions in ErbB-family member degradation, is a critical tumor modifier at this locus. We analyzed 971 stage I/II breast tumors using Affymetrix Oncoscan molecular inversion probe arrays that include 12 probes located within LRIG1. Copy number results were validated against gene expression data available in the public database. By partitioning the LRIG1 probes nearest exon 12/13, we confirm a breakpoint in the gene and show that gains and losses in the subregions differ by tumor and patient characteristics including race/ethnicity. In analyses adjusted for known prognostic factors, loss of LRIG1 was independently associated with risk of any relapse (HR, 1.90; 95% CI, 1.32-2.73), relapse≥5 years (HR, 2.39; 95% CI, 1.31-4.36), and death (HR, 1.55; 95% CI, 1.11-2.16). Analyses of copy number across chromosome 3, as well as expression data from pooled, publicly available datasets, corroborated the hypothesis of an elevated and persistent risk among cases with loss of or low LRIG1. We concluded that loss/low expression of LRIG1 is an independent risk factor for breast cancer metastasis and death in stage I/II patients. Increased hazard in patients with loss/low LRIG1 persists years after diagnosis, suggesting that LRIG1 is acting as a critical suppressor of tumor metastasis and is an early clinical indicator of risk for late recurrences in otherwise low-risk patients.

Personal history of diabetes, genetic susceptibility to diabetes, and risk of brain glioma: a pooled analysis of observational studies

BACKGROUND

Brain glioma is a relatively rare and fatal malignancy in adulthood with few known risk factors. Some observational studies have reported inverse associations between diabetes and subsequent glioma risk, but possible mechanisms are unclear.

METHODS

We conducted a pooled analysis of original data from five nested case-control studies and two case-control studies from the United States and China that included 962 glioma cases and 2,195 controls. We examined self-reported diabetes history in relation to glioma risk, as well as effect modification by seven glioma risk-associated single-nucleotide polymorphisms (SNP). We also examined the associations between 13 diabetes risk-associated SNPs, identified from genome-wide association studies, and glioma risk. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using multivariable-adjusted logistic regression models.

RESULTS

We observed a 42% reduced risk of glioma for individuals with a history of diabetes (OR = 0.58; 95% CI, 0.40-0.84). The association did not differ by sex, study design, or after restricting to glioblastoma, the most common histological subtype. We did not observe any significant per-allele trends among the 13 diabetes-related SNPs examined in relation to glioma risk.

CONCLUSION

These results support an inverse association between diabetes history and glioma risk. The role of genetic susceptibility to diabetes cannot be excluded, and should be pursued in future studies together with other factors that might be responsible for the diabetes-glioma association.

IMPACT

These data suggest the need for studies that can evaluate, separately, the association between type 1 and type 2 diabetes and subsequent risk of adult glioma.

Association between adult height, genetic susceptibility and risk of glioma

BACKGROUND

Some, but not all, observational studies have suggested that taller stature is associated with a significant increased risk of glioma. In a pooled analysis of observational studies, we investigated the strength and consistency of this association, overall and for major sub-types, and investigated effect modification by genetic susceptibility to the disease.

METHODS

We standardized and combined individual-level data on 1354 cases and 4734 control subjects from 13 prospective and 2 case-control studies. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) for glioma and glioma sub-types were estimated using logistic regression models stratified by sex and adjusted for birth cohort and study. Pooled ORs were additionally estimated after stratifying the models according to seven recently identified glioma-related genetic variants.

RESULTS

Among men, we found a positive association between height and glioma risk (≥ 190 vs 170-174 cm, pooled OR = 1.70, 95% CI: 1.11-2.61; P-trend = 0.01), which was slightly stronger after restricting to cases with glioblastoma (pooled OR = 1.99, 95% CI: 1.17-3.38; P-trend = 0.02). Among women, these associations were less clear (≥ 175 vs 160-164 cm, pooled OR for glioma = 1.06, 95% CI: 0.70-1.62; P-trend = 0.22; pooled OR for glioblastoma = 1.36, 95% CI: 0.77-2.39; P-trend = 0.04). In general, we did not observe evidence of effect modification by glioma-related genotypes on the association between height and glioma risk.

CONCLUSION

An association of taller adult stature with glioma, particularly for men and stronger for glioblastoma, should be investigated further to clarify the role of environmental and genetic determinants of height in the etiology of this disease.

Description of selected characteristics of familial glioma patients - results from the Gliogene Consortium

BACKGROUND

While certain inherited syndromes (e.g. Neurofibromatosis or Li-Fraumeni) are associated with an increased risk of glioma, most familial gliomas are non-syndromic. This study describes the demographic and clinical characteristics of the largest series of non-syndromic glioma families ascertained from 14 centres in the United States (US), Europe and Israel as part of the Gliogene Consortium.

METHODS

Families with 2 or more verified gliomas were recruited between January 2007 and February 2011. Distributions of demographic characteristics and clinical variables of gliomas in the families were described based on information derived from personal questionnaires.

FINDINGS

The study population comprised 841 glioma patients identified in 376 families (9797 individuals). There were more cases of glioma among males, with a male to female ratio of 1.25. In most families (83%), 2 gliomas were reported, with 3 and 4 gliomas in 13% and 3% of the families, respectively. For families with 2 gliomas, 57% were among 1st-degree relatives, and 31.5% among 2nd-degree relatives. Overall, the mean (±standard deviation [SD]) diagnosis age was 49.4 (±18.7) years. In 48% of families with 2 gliomas, at least one was diagnosed at <40y, and in 12% both were diagnosed under 40y of age. Most of these families (76%) had at least one grade IV glioblastoma multiforme (GBM), and in 32% both cases were grade IV gliomas. The most common glioma subtype was GBM (55%), followed by anaplastic astrocytoma (10%) and oligodendroglioma (8%). Individuals with grades I-II were on average 17y younger than those with grades III-IV.

INTERPRETATION

Familial glioma cases are similar to sporadic cases in terms of gender distribution, age, morphology and grade. Most familial gliomas appear to comprise clusters of two cases suggesting low penetrance, and that the risk of developing additional gliomas is probably low. These results should be useful in the counselling and clinical management of individuals with a family history of glioma.

hTERT cancer risk genotypes are associated with telomere length

Telomere biology is associated with cancer initiation and prognosis. Collected data suggest that blood cell telomere length (TL) can change over time, which may be related to development of common disorders, such as cardiovascular diseases and cancer. Recently, single nucleotide polymorphisms in the region of the human telomerase reverse transcriptase (hTERT) gene were associated with various malignancies, including glioma, lung and urinary bladder cancer, and telomerase RNA gene hTERC genotypes were recently linked to TL. In the present study a hypothetical association between identified genotypes in hTERT and hTERC genes and TL were investigated. We analyzed 21 polymorphisms, covering 90% of the genetic variance, in the hTERT gene, two genetic variants in hTERC, and relative TL(RTL) at average age 50 and 60 in 959 individuals with repeated blood samples. Mean RTL at age 60 was associated with four genetic variants of the hTERT gene (rs2736100, rs2853672, rs2853677, and rs2853676), two of which reported to be associated with cancer risk. Two alleles (rs12696304, rs16847897) near the hTERC gene were confirmed as also being associated with RTL at age 60. Our data suggest that hTERT and hTERC genotypes have an impact on TL of potential relevance and detectable first at higher ages, which gives us further insight to the complex regulation of TL.

Genome-wide association study of glioma and meta-analysis

Gliomas account for approximately 80 % of all primary malignant brain tumors and, despite improvements in clinical care over the last 20 years, remain among the most lethal tumors, underscoring the need for gaining new insights that could translate into clinical advances. Recent genome-wide association studies (GWAS) have identified seven new susceptibility regions. We conducted a new independent GWAS of glioma using 1,856 cases and 4,955 controls (from 14 cohort studies, 3 case-control studies, and 1 population-based case-only study) and found evidence of strong replication for three of the seven previously reported associations at 20q13.33 (RTEL), 5p15.33 (TERT), and 9p21.3 (CDKN2BAS), and consistent association signals for the remaining four at 7p11.2 (EGFR both loci), 8q24.21 (CCDC26) and 11q23.3 (PHLDB1). The direction and magnitude of the signal were consistent for samples from cohort and case-control studies, but the strength of the association was more pronounced for loci rs6010620 (20q,13.33; RTEL) and rs2736100 (5p15.33, TERT) in cohort studies despite the smaller number of cases in this group, likely due to relatively more higher grade tumors being captured in the cohort studies. We further examined the 85 most promising single nucleotide polymorphism (SNP) markers identified in our study in three replication sets (5,015 cases and 11,601 controls), but no new markers reached genome-wide significance. Our findings suggest that larger studies focusing on novel approaches as well as specific tumor subtypes or subgroups will be required to identify additional common susceptibility loci for glioma risk.

Insight in glioma susceptibility through an analysis of 6p22.3, 12p13.33-12.1, 17q22-23.2 and 18q23 SNP genotypes in familial and non-familial glioma

The risk of glioma has consistently been shown to be increased twofold in relatives of patients with primary brain tumors (PBT). A recent genome-wide linkage study of glioma families provided evidence for a disease locus on 17q12-21.32, with the possibility of four additional risk loci at 6p22.3, 12p13.33-12.1, 17q22-23.2, and 18q23. To identify the underlying genetic variants responsible for the linkage signals, we compared the genotype frequencies of 5,122 SNPs mapping to these five regions in 88 glioma cases with and 1,100 cases without a family history of PBT (discovery study). An additional series of 84 familial and 903 non-familial cases were used to replicate associations. In the discovery study, 12 SNPs showed significant associations with family history of PBT (P < 0.001). In the replication study, two of the 12 SNPs were confirmed: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.031) and 17q12-21.32 SPOP rs650461 (P = 0.025). In the combined analysis of discovery and replication studies, the strongest associations were attained at four SNPs: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.0001), SOX5 rs7305773 (P = 0.0001) and STKY1 rs2418087 (P = 0.0003), and 17q12-21.32 SPOP rs6504618 (P = 0.0006). Further, a significant gene-dosage effect was found for increased risk of family history of PBT with these four SNPs in the combined data set (P(trend) <1.0 × 10(-8)). The results support the linkage finding that some loci in the 12p13.33-12.1 and 17q12-q21.32 may contribute to gliomagenesis and suggest potential target genes underscoring linkage signals.

Detectable clonal mosaicism and its relationship to aging and cancer

In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 × 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 × 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases.

A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits

Pooling genome-wide association studies (GWASs) increases power but also poses methodological challenges because studies are often heterogeneous. For example, combining GWASs of related but distinct traits can provide promising directions for the discovery of loci with small but common pleiotropic effects. Classical approaches for meta-analysis or pooled analysis, however, might not be suitable for such analysis because individual variants are likely to be associated with only a subset of the traits or might demonstrate effects in different directions. We propose a method that exhaustively explores subsets of studies for the presence of true association signals that are in either the same direction or possibly opposite directions. An efficient approximation is used for rapid evaluation of p values. We present two illustrative applications, one for a meta-analysis of separate case-control studies of six distinct cancers and another for pooled analysis of a case-control study of glioma, a class of brain tumors that contains heterogeneous subtypes. Both the applications and additional simulation studies demonstrate that the proposed methods offer improved power and more interpretable results when compared to traditional methods for the analysis of heterogeneous traits. The proposed framework has applications beyond genetic association studies.

DNA-repair gene variants are associated with glioblastoma survival

Patient outcome from glioma may be influenced by germline variation. Considering the importance of DNA repair in cancer biology as well as in response to treatment, we studied the relationship between 1458 SNPs, which captured the majority of the common genetic variation in 136 DNA repair genes, in 138 glioblastoma samples from Sweden and Denmark. We confirmed our findings in an independent cohort of 121 glioblastoma patients from the UK. Our analysis revealed nine SNPs annotating MSH2, RAD51L1 and RECQL4 that were significantly (p < 0.05) associated with glioblastoma survival.

Genome-wide high-density SNP linkage search for glioma susceptibility loci: results from the Gliogene Consortium

Gliomas, which generally have a poor prognosis, are the most common primary malignant brain tumors in adults. Recent genome-wide association studies have shown that inherited susceptibility plays a role in the development of glioma. Although first-degree relatives of patients exhibit a two-fold increased risk of glioma, the search for susceptibility loci in familial forms of the disease has been challenging because the disease is relatively rare, fatal, and heterogeneous, making it difficult to collect sufficient biosamples from families for statistical power. To address this challenge, the Genetic Epidemiology of Glioma International Consortium (Gliogene) was formed to collect DNA samples from families with two or more cases of histologically confirmed glioma. In this study, we present results obtained from 46 U.S. families in which multipoint linkage analyses were undertaken using nonparametric (model-free) methods. After removal of high linkage disequilibrium single-nucleotide polymorphism, we obtained a maximum nonparametric linkage score (NPL) of 3.39 (P = 0.0005) at 17q12-21.32 and the Z-score of 4.20 (P = 0.000007). To replicate our findings, we genotyped 29 independent U.S. families and obtained a maximum NPL score of 1.26 (P = 0.008) and the Z-score of 1.47 (P = 0.035). Accounting for the genetic heterogeneity using the ordered subset analysis approach, the combined analyses of 75 families resulted in a maximum NPL score of 3.81 (P = 0.00001). The genomic regions we have implicated in this study may offer novel insights into glioma susceptibility, focusing future work to identify genes that cause familial glioma.

Concentrations of IGF-I and IGFBP-3 and brain tumor risk in the European Prospective Investigation into Cancer and Nutrition

BACKGROUND

Insulin-like growth factor-1 (IGF-I) is important in normal brain development but in the adult brain, IGF-I overexpression may be a risk factor for tumor development.

METHODS

We examined the association between circulating concentrations of IGF-I and IGFBP-3 in relation to risk of gliomas (74 low-grade, 206 high-grade gliomas), meningiomas (n = 174) and acoustic neuromas (n = 49) by using a case-control design nested in the European Prospective Investigation into Cancer and Nutrition. IGF-I and IGFBP-3 were measured by ELISAs.Conditional logistic regression was used to compute ORs and corresponding 95% CIs.

RESULTS

The risk of low-grade gliomas was elevated with increased IGF-I (OR = 3.60, 95% CI: 1.11-11.7; top vs. bottom quartile) and decreased with elevated IGFBP-3 concentrations (OR = 0.28, 95% CI: 0.09-0.84) after mutual adjustment of these two factors; these results became nonsignificant after exclusion of the first year of follow-up. No association was observed for high-grade gliomas or meningiomas. Both high IGF-I and IGFBP-3 concentrations were associated with risk of acoustic neuromas (IGF-I: OR = 6.63, 95% CI: 2.27-19.4, top vs. bottom tertile; IGFBP-3: OR = 7.07, 95% CI: 2.32-21.6), even after excluding the first year of follow-up.

CONCLUSION

High concentrations of IGF-I might be positively associated with risk of low-grade gliomas and acoustic neuromas, although we cannot exclude reverse causation, in particular for low-grade gliomas.

IMPACT

Factors of the IGF axis might be involved in the etiology of some types of brain tumors.

Human immunoglobulin G levels of viruses and associated glioma risk

Few consistent etiological factors have been identified for primary brain tumors. Inverse associations to asthma and low levels of varicella-zoster virus, immunoglobulin (Ig) levels in prevalent cases have indicted a role for the immune system in the development of glioma. Because samples from prevalent cases of glioma could be influenced by treatments such as steroids and chemotherapy, we investigated pre-diagnostic samples from three large Scandinavian cohorts. To test the hypothesis that immune response levels to these viruses are associated etiologically with glioma risk, we investigated pre-diagnostic immunoglobulin levels for cytomegalovirus (CMV), varicella-zoster virus (VZV), adenovirus (Ad), and Epstein-Barr virus (EBV) including the nuclear antigen (EBNA1) using plasma samples from 197 cases of adult glioma and 394 controls collected from population-based cohorts in Sweden and Denmark. Low VZV IgG levels were marginally significantly more common in glioma cases than the controls (odds ratio (OR) = 0.68, 95% CI 0.41–1.13) for the fourth compared with the first quartile (p = 0.06 for trend). These results were more prominent when analyzing cases with blood sampling at least 2 years before diagnosis (OR = 0.63, 95% CI 0.37–1.08) (p = 0.03). No association with glioma risk was observed for CMV, EBV, and adenovirus.

Anthropometric measures, physical activity, and risk of glioma and meningioma in a large prospective cohort study

Body fatness has been associated with increased risk of a number of hormone-dependent cancers. Recent studies suggest that body mass index (BMI) may be related to meningiomas, which are more common in women than men, and for which estrogens are believed to play a role. Using data from a large European propective cohort, 203 incident cases of meningioma and 340 cases of glioma were included in the analysis for measures of body fat, height, and physical activity among 380,775 participants. All analyses were conducted using Cox proportional hazards model and controlling for age, sex, country, and education. A 71% increase in risk of meningioma was observed among men and women in the top quartile of waist circumference (HR = 1.71, 95% CI = 1.08-2.73, P(trend) = 0.01). A positive association was also observed for BMI and meningioma (HR = 1.48, 95% CI = 0.98-2.23, for BMI ≥30 compared with a BMI of 20-24.9, P(trend) = 0.05). An association with height and meningioma was also suggestive (HR = 1.24, 95% 0.96-1.51, for each 10 cm increase). In contrast, no associations were observed for height and different measures of body fat and risk of glioma. Physical activity was not related to either type of brain tumors. Results from this study support an increase in risk of meningioma with higher body fatness among both men and women. No association was observed between anthropometric measures and risk of glioma.

Risk factors for oligodendroglial tumors: a pooled international study

Oligodendroglial tumors are rare subtypes of brain tumors and are often combined with other glial tumors in epidemiological analyses. However, different demographic associations and clinical characteristics suggest potentially different risk factors. The purpose of this study was to investigate possible risk factors for oligodendroglial tumors (including oligodendroglioma, anaplastic oligodendroglioma, and mixed glioma). Data from 7 case-control studies (5 US and 2 Scandinavian) were pooled. Unconditional logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusted for age group, gender, and study site. Data on 617 cases and 1260 controls were available for analyses. Using data from all 7 studies, history of allergies and/or asthma was associated with a decreased risk of anaplastic oligodendroglioma (OR = 0.6; 95% CI: 0.4-0.9), and history of asthma only was associated with a decreased risk of oligodendroglioma (OR = 0.5; 95% CI: 0.3-0.9) and anaplastic oligodendroglioma (OR = 0.3; 95% CI: 0.1-0.9). A family history of brain tumors was associated with an increased risk of anaplastic oligodendroglioma (OR = 2.2; 95% CI: 1.1-4.5). Having had chicken pox was associated with a decreased risk of oligodendroglioma (OR = 0.6; 95% CI: 0.4-0.9) and anaplastic oligodendroglioma (OR = 0.5; 95% CI: 0.3-0.9) in the US studies. Although there is some overlap in risk factors between oligodendroglial tumors and gliomas as a group, it is likely that additional factors specific to oligodendroglial tumors have yet to be identified. Large, multi-institution international studies will be necessary to better characterize these etiological risk factors.

Familial aggregation of glioma: a pooled analysis

In genome-wide association studies, inherited risk of glioma has been demonstrated for rare familial syndromes and with common variants from 3-5 chromosomal regions. To assess the degree of familial aggregation of glioma, the authors performed a pooled analysis of data from 2 large glioma case-control studies in the United States (MD Anderson Cancer Center, Houston, Texas (1994-2006) and University of California, San Francisco (1991-2004)) and from the Swedish Cancer Registry (1958-2006) to measure excess cases of cancer among first-degree relatives of glioma probands. This analysis included 20,377 probands with glioma and 52,714 first-degree relatives. No overall increase was found in the expected number of cancers among family members; however, there were 77% more gliomas than expected. There were also significantly more sarcoma and melanoma cases than expected, which is supported by evidence in the literature, whereas there were significantly fewer-than-expected cases of leukemia, non-Hodgkin lymphoma, and bladder, lung, pancreatic, prostate, and uterine cancers. This large pooled analysis provided sufficient numbers of related family members to examine the genetic mechanisms involved in the aggregation of glioma with other cancers in these families. However, misclassification due to unvalidated cancers among family members could account for the differences seen by study site.

Coffee and tea intake and risk of brain tumors in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort study

BACKGROUND

In a recent US cohort study, total coffee and tea consumption was inversely associated with risk of glioma, and experimental studies showed that caffeine can slow the invasive growth of glioblastoma.

OBJECTIVE

The objective was to examine the relation between coffee and tea intake and the risk of glioma and meningioma in a large European cohort study, the European Prospective Investigation into Cancer and Nutrition (EPIC).

DESIGN

Data on coffee and tea intake were collected from men and women recruited into the EPIC cohort study. Over an average of 8.5 y of follow-up, 343 cases of glioma and 245 cases of meningioma were newly diagnosed in 9 countries. We used Cox proportional hazards models to examine the relation between coffee and tea and brain tumors.

RESULTS

We observed no associations between coffee, tea, or combined coffee and tea consumption and risk of either type of brain tumor when using quantiles based on country-specific distributions of intake. However, a significant inverse association was observed for glioma risk among those consuming ≥100 mL coffee and tea per day compared with those consuming <100 mL/d (hazard ratio: 0.66; 95% CI: 0.44, 0.97; P = 0.03). The association was slightly stronger in men (hazard ratio: 0.59; 95% CI: 0.34, 1.01) than in women (hazard ratio: 0.74; 95% CI: 0.42, 1.31), although neither was statistically significant.

CONCLUSIONS

In this large cohort study, we observed an inverse association between total coffee and tea consumption and risk of glioma that was consistent with the findings of a recent study. These findings, if further replicated in other studies, may provide new avenues of research on gliomas.

Reproductive factors and exogenous hormone use in relation to risk of glioma and meningioma in a large European cohort study

BACKGROUND

The etiologies of glioma and meningioma tumors are largely unknown. Although reproductive hormones are thought to influence the risk of these tumors, epidemiologic data are not supportive of this hypothesis; however, few cohort studies have published on this topic. We examined the relation between reproductive factors and the risk of glioma and meningioma among women in the European Prospective Investigation into Cancer and Nutrition (EPIC).

METHODS

After a mean of 8.4 years of follow-up, 193 glioma and 194 meningioma cases were identified among 276,212 women. Information on reproductive factors and hormone use was collected at baseline. Cox proportional hazard regression was used to determine hazard ratios (HR) and 95% confidence intervals (95% CI).

RESULTS

No associations were observed between glioma or meningioma risk and reproductive factors, including age at menarche, parity, age at first birth, menopausal status, and age at menopause. A higher risk of meningioma was observed among postmenopausal women who were current users of hormone replacement therapy (HR, 1.79; 95% CI, 1.18-2.71) compared with never users. Similarly, current users of oral contraceptives were at higher risk of meningioma than never users (HR, 3.61; 95% CI, 1.75-7.46).

CONCLUSION

Our results do not support a role for estrogens and glioma risk. Use of exogenous hormones, especially current use, seems to increase meningioma risk. However, these findings could be due to diagnostic bias and require confirmation.

IMPACT

Elucidating the role of hormones in brain tumor development has important implications and needs to be further examined using biological measurements.

Polymorphisms of LIG4, BTBD2, HMGA2, and RTEL1 genes involved in the double-strand break repair pathway predict glioblastoma survival

PURPOSE

Glioblastoma (GBM) is the most common and aggressive type of glioma and has the poorest survival. However, a small percentage of patients with GBM survive well beyond the established median. Therefore, identifying the genetic variants that influence this small number of unusually long-term survivors may provide important insight into tumor biology and treatment.

PATIENTS AND METHODS

Among 590 patients with primary GBM, we evaluated associations of survival with the 100 top-ranking glioma susceptibility single nucleotide polymorphisms from our previous genome-wide association study using Cox regression models. We also compared differences in genetic variation between short-term survivors (STS; <or= 12 months) and long-term survivors (LTS; >or= 36 months), and explored classification and regression tree analysis for survival data. We tested results using two independent series totaling 543 GBMs.

RESULTS

We identified LIG4 rs7325927 and BTBD2 rs11670188 as predictors of STS in GBM and CCDC26 rs10464870 and rs891835, HMGA2 rs1563834, and RTEL1 rs2297440 as predictors of LTS. Further survival tree analysis revealed that patients >or= 50 years old with LIG4 rs7325927 (V) had the worst survival (median survival time, 1.2 years) and exhibited the highest risk of death (hazard ratio, 17.53; 95% CI, 4.27 to 71.97) compared with younger patients with combined RTEL1 rs2297440 (V) and HMGA2 rs1563834 (V) genotypes (median survival time, 7.8 years).

CONCLUSION

Polymorphisms in the LIG4, BTBD2, HMGA2, and RTEL1 genes, which are involved in the double-strand break repair pathway, are associated with GBM survival.