Soft-tissue sarcoma in adolescents and young adults compared with older adults: A report among 5000 patients from the Scandinavian Sarcoma Group Central Register.

BACKGROUND: In recent years, there has been growing awareness of the distinct characteristics of adolescents and young adults (AYA) diagnosed with cancer. Soft-tissue sarcoma (STS) accounts for approximately 1% of all cancers diagnosed in adults and 8% of cancers diagnosed in AYA. To the best of our knowledge, only a few sarcoma registers include data regarding histological subtype, age at diagnosis, and detailed clinical information. Therefore, little is known regarding clinical presentation and outcomes in AYA diagnosed with STS. METHODS: Using the Scandinavian Sarcoma Group Central Register, data were obtained regarding 4977 patients who were diagnosed with STS for the period between 1986 and 2011. AYA (those aged 18-39 years) were compared with older adults (OA; those aged 40-80 years) with respect to clinical presentation, treatment, and outcome. RESULTS: There were 868 AYA and 4109 OA. Overall and by STS subtype, there were significant differences noted between AYA and OA with regard to presentation, treatment, and survival. The distribution of STS subtypes was different between OA and AYA (eg, OA were more likely to be diagnosed with malignant fibrous histiocytoma compared with AYA [34% vs 16%; P < .001]). OA also were more likely to have tumors measuring ≥5 cm (68% vs 56%; P < .001) and a higher malignancy grade (75% vs 67%; P < .001). In the majority of STS subtypes AYA had significantly better overall survival and less disease recurrence compared with OA, but this finding was not true for those with malignant peripheral nerve sheath tumors. CONCLUSIONS: There are several differences between AYA and OA with STS with regard to presentation, treatment, and survival, and such differences must be taken into consideration when designing clinical trials. Additional work also is needed to characterize the potential biological mechanisms underlying these differences.

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.

Influence of obesity-related risk factors in the aetiology of glioma.

BACKGROUND: Obesity and related factors have been implicated as possible aetiological factors for the development of glioma in epidemiological observation studies. We used genetic markers in a Mendelian randomisation framework to examine whether obesity-related traits influence glioma risk. This methodology reduces bias from confounding and is not affected by reverse causation. METHODS: Genetic instruments were identified for 10 key obesity-related risk factors, and their association with glioma risk was evaluated using data from a genome-wide association study of 12,488 glioma patients and 18,169 controls. The estimated odds ratio of glioma associated with each of the genetically defined obesity-related traits was used to infer evidence for a causal relationship. RESULTS: No convincing association with glioma risk was seen for genetic instruments for body mass index, waist-to-hip ratio, lipids, type-2 diabetes, hyperglycaemia or insulin resistance. Similarly, we found no evidence to support a relationship between obesity-related traits with subtypes of glioma-glioblastoma (GBM) or non-GBM tumours. CONCLUSIONS: This study provides no evidence to implicate obesity-related factors as causes of glioma.

Impact of atopy on risk of glioma: a Mendelian randomisation study.

BACKGROUND: An inverse relationship between allergies with glioma risk has been reported in several but not all epidemiological observational studies. We performed an analysis of genetic variants associated with atopy to assess the relationship with glioma risk using Mendelian randomisation (MR), an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations. METHODS: Two-sample MR was undertaken using genome-wide association study data. We used single nucleotide polymorphisms (SNPs) associated with atopic dermatitis, asthma and hay fever, IgE levels, and self-reported allergy as instrumental variables. We calculated MR estimates for the odds ratio (OR) for each risk factor with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighting (IVW), maximum likelihood estimation (MLE), weighted median estimate (WME) and mode-based estimate (MBE) methods. Violation of MR assumptions due to directional pleiotropy were sought using MR-Egger regression and HEIDI-outlier analysis. RESULTS: Under IVW, MLE, WME and MBE methods, associations between glioma risk with asthma and hay fever, self-reported allergy and IgE levels were non-significant. An inverse relationship between atopic dermatitis and glioma risk was found by IVW (OR 0.96, 95% confidence interval (CI) 0.93-1.00, P = 0.041) and MLE (OR 0.96, 95% CI 0.94-0.99, P = 0.003), but not by WME (OR 0.96, 95% CI 0.91-1.01, P = 0.114) or MBE (OR 0.97, 95% CI 0.92-1.02, P = 0.194). CONCLUSIONS: Our investigation does not provide strong evidence for relationship between atopy and the risk of developing glioma, but findings do not preclude a small effect in relation to atopic dermatitis. Our analysis also serves to illustrate the value of using several MR methods to derive robust conclusions.

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.

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.

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.

Genome-wide Polygenic Risk Scores Predict Risk of Glioma and Molecular Subtypes.

BACKGROUND: Polygenic risk scores (PRS) aggregate the contribution of many risk variants to provide a personalized genetic susceptibility profile. Since sample sizes of glioma genome-wide association studies (GWAS) remain modest, there is a need to efficiently capture genetic risk using available data. METHODS: We applied a method based on continuous shrinkage priors (PRS-CS) to model the joint effects of over 1 million common variants on disease risk and compared this to an approach (PRS-CT) that only selects a limited set of independent variants that reach genome-wide significance (P<5×10-8). PRS models were trained using GWAS stratified by histological (10,346 cases, 14,687 controls) and molecular subtype (2,632 cases, 2,445 controls), and validated in two independent cohorts. RESULTS: PRS-CS was generally more predictive than PRS-CT with a median increase in explained variance (R2) of 24% (interquartile range=11-30%) across glioma subtypes. Improvements were pronounced for glioblastoma (GBM), with PRS-CS yielding larger odds ratios (OR) per standard deviation (OR=1.93, P=2.0×10-54 vs. OR=1.83, P=9.4×10-50) and higher explained variance (R2=2.82% vs. R2=2.56%). Individuals in the 80th percentile of the PRS-CS distribution had significantly higher risk of GBM (0.107%) at age 60 compared to those with average PRS (0.046%, P=2.4×10-12). Lifetime absolute risk reached 1.18% for glioma and 0.76% for IDH wildtype tumors for individuals in the 95th PRS percentile. PRS-CS augmented the classification of IDH mutation status in cases when added to demographic factors (AUC=0.839 vs. AUC=0.895, PΔAUC=6.8×10-9). CONCLUSIONS: Genome-wide PRS has potential to enhance the detection of high-risk individuals and help distinguish between prognostic glioma subtypes.

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.

The genomic landscape of familial glioma.

Glioma is a rare brain tumor with a poor prognosis. Familial glioma is a subset of glioma with a strong genetic predisposition that accounts for approximately 5% of glioma cases. We performed whole-genome sequencing on an exploratory cohort of 203 individuals from 189 families with a history of familial glioma and an additional validation cohort of 122 individuals from 115 families. We found significant enrichment of rare deleterious variants of seven genes in both cohorts, and the most significantly enriched gene was HERC2 (P = 0.0006). Furthermore, we identified rare noncoding variants in both cohorts that were predicted to affect transcription factor binding sites or cause cryptic splicing. Last, we selected a subset of discovered genes for validation by CRISPR knockdown screening and found that DMBT1, HP1BP3, and ZCH7B3 have profound impacts on proliferation. This study performs comprehensive surveillance of the genomic landscape of familial glioma.

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.

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.

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.

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.

Analysis of DNA repair gene polymorphisms and survival in low-grade and anaplastic gliomas.

The purpose of this study was to explore the variation in DNA repair genes in adults with WHO grade II and III gliomas and their relationship to patient survival. We analysed a total of 1,458 tagging single-nucleotide polymorphisms (SNPs) that were selected to cover DNA repair genes, in 81 grade II and grade III gliomas samples, collected in Sweden and Denmark. The statistically significant genetic variants from the first dataset (P < 0.05) were taken forward for confirmation in a second dataset of 72 grade II and III gliomas from northern UK. In this dataset, eight gene variants mapping to five different DNA repair genes (ATM, NEIL1, NEIL2, ERCC6 and RPA4) which were associated with survival. Finally, these eight genetic variants were adjusted for treatment, malignancy grade, patient age and gender, leaving one variant, rs4253079, mapped to ERCC6, with a significant association to survival (OR 0.184, 95% CI 0.054-0.63, P = 0.007). We suggest a possible novel association between rs4253079 and survival in this group of patients with low-grade and anaplastic gliomas that needs confirmation in larger datasets.

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.

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.

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; andInflammatory 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, 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.

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.