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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

Genome-wide association studies (GWAS) have contributed to our understanding of glioma susceptibility. To date, 25 risk loci for development of any of the glioma subtypes are known. However, GWAS studies reveal little about the molecular processes that lead to increased risk, especially for non-coding single nucleotide polymorphisms (SNP). A particular SNP in intron 2 of LRIG1, rs11706832, has been shown to increase the susceptibility for IDH1 mutated low-grade gliomas (LGG). Leucine-rich repeats and immunoglobulin-like domains protein 1 (LRIG1) is important in cancer development as it negatively regulates the epidermal growth factor receptor (EGFR); however, the mechanism responsible for this particular risk SNP and its potential effect on LRIG1 are not known. Using CRISPR-CAS9, we edited rs11706832 in HEK293T cells. Four HEK293T clones with the risk allele were compared to four clones with the non-risk allele for LRIG1 and SLC25A26 gene expression using RT-qPCR, for global gene expression using RNA-seq, and for metabolites using gas chromatography-mass spectrometry (GC-MS). The experiment did not reveal any significant effect of the SNP on the expression levels or splicing patterns of LRIG1 or SLC25A26. The global gene expression analysis revealed that the risk allele C was associated with upregulation of several mitochondrial genes. Gene enrichment analysis of 74 differentially expressed genes in the genome revealed a significant enrichment of type I interferon response genes, where many genes were downregulated for the risk allele C. Gene expression data of IDH1 mutated LGGs from the cancer genome atlas (TCGA) revealed a similar under expression of type I interferon genes associated with the risk allele. This study found the expression levels and splicing patterns of LRIG1 and SLC25A26 were not affected by the SNP in HEK293T cells. However, the risk allele was associated with a downregulation of genes involved in the innate immune response both in the HEK293T cells and in the LGG data from TCGA., (© 2023. The Author(s).)

Background: Understanding the trajectory and development of disease is important and the knowledge can be used to find novel targets for therapy and new diagnostic tools for early diagnosis., Methods: Large cohorts from different parts of the world are unique assets for research as they have systematically collected plasma and DNA over long-time periods in healthy individuals, sometimes even with repeated samples. Over time, the population in the cohort are diagnosed with many different diseases, including brain tumors., Results: Recent studies have detected genetic variants that are associated with increased risk of glioblastoma and lower grade gliomas specifically. The impact for genetic markers to predict disease in a healthy population has been deemed low, and a relevant question is if the genetic variants for glioma are associated with risk of disease or partly consist of genes associated to survival. Both metabolite and protein spectra are currently being explored for early detection of cancer., Conclusions: We here present a focused review of studies of genetic variants, metabolomics, and proteomics studied in prediagnostic glioma samples and discuss their potential in early diagnostics., (© The Author(s) 2022. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Hip fracture is the clinically most important fracture, but the genetic architecture of hip fracture is unclear. Here, we perform a large-scale hip fracture genome-wide association study meta-analysis and Mendelian randomization study using five cohorts from European biobanks. The results show that five genetic signals associate with hip fractures. Among these, one signal associates with falls, but not with bone mineral density (BMD), while four signals are in loci known to be involved in bone biology. Mendelian randomization analyses demonstrate a strong causal effect of decreased femoral neck BMD and moderate causal effects of Alzheimer's disease and having ever smoked regularly on risk of hip fractures. The substantial causal effect of decreased femoral neck BMD on hip fractures in both young and old subjects and in both men and women supports the use of change in femoral neck BMD as a surrogate outcome for hip fractures in clinical trials., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Gliomas are complex tumors with several genetic aberrations and diverse metabolic programs contributing to their aggressive phenotypes and poor prognoses. This study defines key metabolic features that can be used to differentiate between glioma subtypes, with potential for improved diagnostics and subtype targeted therapy., Methods: Cross-platform global metabolomic profiling coupled with clinical, genetic, and pathological analysis of glioma tissue from 224 tumors-oligodendroglioma (n = 31), astrocytoma (n = 31) and glioblastoma (n = 162)-were performed. Identified metabolic phenotypes were evaluated in accordance with the WHO classification, IDH-mutation, 1p/19q-codeletion, WHO-grading 2-4, and MGMT promoter methylation., Results: Distinct metabolic phenotypes separate all six analyzed glioma subtypes. IDH-mutated subtypes, expressing 2-hydroxyglutaric acid, were clearly distinguished from IDH-wildtype subtypes. Considerable metabolic heterogeneity outside of the mutated IDH pathway were also evident, with key metabolites being high expression of glycerophosphates, inositols, monosaccharides, and sugar alcohols and low levels of sphingosine and lysoglycerophospholipids in IDH-mutants. Among the IDH-mutated subtypes, we observed high levels of amino acids, especially glycine and 2-aminoadipic acid, in grade 4 glioma, and N-acetyl aspartic acid in low-grade astrocytoma and oligodendroglioma. Both IDH-wildtype and mutated oligodendroglioma and glioblastoma were characterized by high levels of acylcarnitines, likely driven by rapid cell growth and hypoxic features. We found elevated levels of 5-HIAA in gliosarcoma and a subtype of oligodendroglioma not yet defined as a specific entity, indicating a previously not described role for the serotonin pathway linked to glioma with bimorphic tissue., Conclusion: Key metabolic differences exist across adult glioma subtypes., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

No strong aetiological factors have been established for glioma aside from genetic mutations and variants, ionising radiation and an inverse relationship with asthmas and allergies. Our aim was to investigate the association between pre-diagnostic immune protein levels and glioma risk. We conducted a case-control study nested in the Northern Sweden Health and Disease Study cohort. We analysed 133 glioma cases and 133 control subjects matched by age, sex and date of blood donation. ELISA or Luminex bead-based multiplex assays were used to measure plasma levels of 19 proteins. Conditional logistic regression models were used to estimate the odds ratios and 95% CIs. To further model the protein trajectories over time, the linear mixed-effects models were conducted. We found that the levels of sVEGFR2, sTNFR2, sIL-2Rα and sIL-6R were associated with glioma risk. After adjusting for the time between blood sample collection and glioma diagnosis, the odds ratios were 1.72 (95% CI = 1.01-2.93), 1.48 (95% CI = 1.01-2.16) and 1.90 (95% CI = 1.14-3.17) for sTNFR2, sIL-2Rα and sIL-6R, respectively. The trajectory of sVEGFR2 concentrations over time was different between cases and controls (p-value = 0.031), increasing for cases (0.8% per year) and constant for controls. Our findings suggest these proteins play important roles in gliomagenesis., (© 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Changes in immune marker levels in the blood could be used to improve the early detection of tumor-associated inflammatory processes. To increase predictiveness and utility in cancer detection, intraindividual long-term stability in cancer-free individuals is critical for biomarker candidates as to facilitate the detection of deviation from the norm., Methods: We assessed intraindividual long-term stability for 19 immune markers (IL10, IL13, TNFα, CXCL13, MCP-3, MIP-1α, MIP-1β, fractalkine, VEGF, FGF-2, TGFα, sIL2Rα, sIL6R, sVEGF-R2, sTNF-R1, sTNF-R2, sCD23, sCD27, and sCD30) in 304 cancer-free individuals. Repeated blood samples were collected up to 20 years apart. Intraindividual reproducibility was assessed by calculating intraclass correlation coefficients (ICC) using a linear mixed model., Results: ICCs indicated fair to good reproducibility (ICCs ≥ 0.40 and < 0.75) for 17 of 19 investigated immune markers, including IL10, IL13, TNFα, CXCL13, MCP-3, MIP-1α, MIP-1β, fractalkine, VEGF, FGF-2, TGFα, sIL2Rα, sIL6R, sTNF-R1, sTNF-R2, sCD27, and sCD30. Reproducibility was strong (ICC ≥ 0.75) for sCD23, while reproducibility was poor (ICC < 0.40) for sVEGF-R2. Using a more stringent criterion for reproducibility (ICC ≥ 0.55), we observed either acceptable or better reproducibility for IL10, IL13, CXCL13, MCP-3, MIP-1α, MIP-1β, VEGF, FGF-2, sTNF-R1, sCD23, sCD27, and sCD30., Conclusions: IL10, IL13, CXCL13, MCP-3, MIP-1α, MIP-1β, VEGF, FGF-2, sTNF-R1, sCD23, sCD27, and sCD30 displayed ICCs consistent with intraindividual long-term stability in cancer-free individuals., Impact: Our data support using these markers in prospective longitudinal studies seeking early cancer detection biomarkers., (©2021 American Association for Cancer Research.)

Introduction: Medulloblastoma is a malignant embryonal tumor of the cerebellum that occurs predominantly in children. To find germline genetic variants associated with medulloblastoma risk, we conducted a genome-wide association study (GWAS) including 244 medulloblastoma cases and 247 control subjects from Sweden and Denmark., Methods: Genotyping was performed using Illumina BeadChips, and untyped variants were imputed using IMPUTE2., Results: Fifty-nine variants in 11 loci were associated with increased medulloblastoma risk (p < 1 × 10 -5 ), but none were statistically significant after adjusting for multiple testing (p < 5 × 10 -8 ). Thirteen of these variants were genotyped, whereas 46 were imputed. Genotyped variants were further investigated in a validation study comprising 249 medulloblastoma cases and 629 control subjects. In the validation study, rs78021424 (18p11.23, PTPRM) was associated with medulloblastoma risk with OR in the same direction as in the discovery cohort (OR T  = 1.59, p validation  = 0.02). We also selected seven medulloblastoma predisposition genes for investigation using a candidate gene approach: APC, BRCA2, PALB2, PTCH1, SUFU, TP53, and GPR161. The strongest evidence for association was found for rs201458864 (PALB2, OR T  = 3.76, p = 3.2 × 10 -4 ) and rs79036813 (PTCH1, OR A  = 0.42, p = 2.6 × 10 -3 )., Conclusion: The results of this study, including a novel potential medulloblastoma risk loci at 18p11.23, are suggestive but need further validation in independent cohorts.

Genome-wide association studies have identified 25 germline genetic loci that increase the risk of glioma. The somatic tumor molecular alterations, including IDH -mutation status and 1p/19q co-deletion, have been included into the WHO 2016 classification system for glioma. To investigate how the germline genetic risk variants correlate with the somatic molecular subtypes put forward by WHO, we performed a meta-analysis that combined findings from 330 Swedish cases and 876 controls with two other recent studies. In total, 5,103 cases and 10,915 controls were included. Three categories of associations were found. First, variants in TERT and TP53 were associated with increased risk of all glioma subtypes. Second, variants in CDKN2B-AS1 , EGFR , and RTEL1 were associated with IDH -wildtype glioma. Third, variants in CCDC26 (the 8q24 locus), C2orf80 (close to IDH ), LRIG1 , PHLDB1 , ETFA , MAML2 and ZBTB16 were associated with IDH -mutant glioma. We therefore propose three etiopathological pathways in gliomagenesis based on germline variants for future guidance of diagnosis and potential functional targets for therapies. Future prospective clinical trials of patients with suspicion of glioma diagnoses, using the genetic variants as biomarkers, are necessary to disentangle how strongly they can predict glioma diagnosis.

Biomarkers reliably predicting progression to multiple myeloma (MM) are lacking. Myeloma risk has been associated with low blood levels of monocyte chemotactic protein-3 (MCP-3), macrophage inflammatory protein-1 alpha (MIP-1α), vascular endothelial growth factor (VEGF), fibroblast growth factor-2 (FGF-2), fractalkine, and transforming growth factor-alpha (TGF-α). In this study, we aimed to replicate these findings and study the individual dynamics of each marker in a prospective longitudinal cohort, thereby examining their potential as markers of myeloma progression. For this purpose, we identified 65 myeloma cases and 65 matched cancer-free controls each with two donated blood samples within the Northern Sweden Health and Disease Study. The first and repeated samples from myeloma cases were donated at a median 13 and 4 years, respectively, before the myeloma was diagnosed. Known risk factors for progression were determined by protein-, and immunofixation electrophoresis, and free light chain assays. We observed lower levels of MCP-3, VEGF, FGF-2, and TGF-α in myeloma patients than in controls, consistent with previous data. We also observed that these markers decreased among future myeloma patients while remaining stable in controls. Decreasing trajectories were noted for TGF-α ( P =2.5 × 10 -4 ) indicating progression to MM. Investigating this, we found that low levels of TGF-α assessed at the time of the repeated sample were independently associated with risk of progression in a multivariable model (hazard ratio = 3.5; P =0.003). TGF-α can potentially improve early detection of MM., (Copyright© 2019 Ferrata Storti Foundation.)

Background: Genome-wide association studies have identified germline genetic variants in 25 genetic loci that increase the risk of developing glioma in adulthood. It is not known if these variants increase the risk of developing glioma in children and adolescents and young adults (AYA). To date, no studies have performed genome-wide analyses to find novel genetic variants associated with glioma risk in children and AYA., Methods: We investigated the association between 8,831,628 genetic variants and risk of glioma in 854 patients diagnosed up to the age of 29 years and 3,689 controls from Sweden and Denmark. Recruitment of patients and controls was population based. Genotyping was performed using Illumina BeadChips, and untyped variants were imputed with IMPUTE2. We selected 41 established adult glioma risk variants for detailed investigation., Results: Three adult glioma risk variants, rs634537, rs2157719, and rs145929329, all mapping to the 9p21.3 ( CDKN2B-AS1 ) locus, were associated with glioma risk in children and AYA. The strongest association was seen for rs634537 (odds ratio G = 1.21; 95% confidence interval = 1.09-1.35; P = 5.8 × 10 -4 ). In genome-wide analysis, an association with risk was suggested for 129 genetic variants ( P <1 × 10 -5 )., Conclusions: Carriers of risk alleles in the 9p21.3 locus have an increased risk of glioma throughout life. The results from genome-wide association analyses require validation in independent cohorts., Impact: Our findings line up with existing evidence that some, although not all, established adult glioma risk variants are associated with risk of glioma in children and AYA. Validation of results from genome-wide analyses may reveal novel susceptibility loci for glioma in children and AYA., (©2019 American Association for Cancer Research.)

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., Competing Interests: The authors have declared that no competing interests exist.

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.

The B-cell activation markers CXCL13, sCD23, sCD27, and sCD30 are associated with future lymphoma risk. However, a lack of information about the individual dynamics of marker-disease association hampers interpretation. In this study, we identified 170 individuals who had donated two prediagnostic blood samples before B-cell lymphoma diagnosis, along with 170 matched cancer-free controls from the Northern Sweden Health and Disease Study. Lymphoma risk associations were investigated by subtype and marker levels measured at baseline, at the time of the repeated sample, and with the rate of change in the marker level. Notably, we observed strong associations between CXCL13, sCD23, sCD27, and sCD30 and lymphoma risk in blood samples collected 15 to 25 years before diagnosis. B-cell activation marker levels increased among future lymphoma cases over time, while remaining stable among controls. Associations between slope and risk were strongest for indolent lymphoma subtypes. We noted a marked association of sCD23 with chronic lymphocytic leukemia (OR Slope = 28, P trend = 7.279 × 10 -10 ). Among aggressive lymphomas, the association between diffuse large B-cell lymphoma risk and slope was restricted to CXCL13. B-cell activation seemed to play a role in B-cell lymphoma development at early stages across different subtypes. Furthermore, B-cell activation presented differential trajectories in future lymphoma patients, mainly driven by indolent subtypes. Our results suggest a utility of these markers in predicting the presence of early occult disease and/or the screening and monitoring of indolent lymphoma in individual patients. Cancer Res; 77(6); 1408-15. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Genome-wide association studies and candidate gene studies have identified several genetic variants that increase glioma risk. The majority of these variants are non-coding and the mechanisms behind the increased risk in carriers are not known. In this study, we hypothesize that some of the established glioma risk variants induce aberrant DNA methylation in the developing tumor, either locally (gene-specific) or globally (genome-wide). In a pilot data set including 77 glioma patients, we used Illumina beadchip technology to analyze genetic variants in blood and DNA methylation in matched tumor samples. To validate our findings, we used data from the Cancer Genome Atlas, including 401 glioblastoma patients. Consensus clustering identified the glioma CpG island methylator phenotype (gCIMP) and two additional subgroups with distinct patterns of global DNA methylation. In the pilot dataset, gCIMP was associated with two genetic variants in CDKN2B-AS1, rs1412829 and rs4977756 (9p21.3, p = 8.1 x 10-7 and 4.8 x 10-5, respectively). The association was in the same direction in the TCGA dataset, although statistically significant only when combining individuals with AG and GG genotypes. We also investigated the relation between glioma risk variants and DNA methylation in the promoter region of genes located within 30 kb of each variant. One association in the pilot dataset, between the TERT risk variant rs2736100 and lower methylation of cg23827991 (in TERT; p = 0.001), was confirmed in the TCGA dataset (p = 0.001). In conclusion, we found an association between rs1412829 and rs4977756 (9p21.3, CDKN2B-AS1) and global DNA methylation pattern in glioma, for which a trend was seen also in the TCGA glioblastoma dataset. We also found an association between rs2736100 (in TERT) and levels of methylation at cg23827991 (localized in the same gene, 3.3 kbp downstream of the risk variant), which was validated in the TCGA dataset. Except for this one association, we did not find strong evidence for gene-specific DNA methylation mediated by glioma risk variants., Competing Interests: The authors have declared that no competing interests exist.

Genetic variants have been associated with the risk of developing glioma, but functional mechanisms on disease phenotypic traits remain to be investigated. One phenotypic trait of glioblastoma is the mutation and amplification of the epidermal growth factor receptor (EGFR) gene. We investigated associations between pre-diagnostic serum protein concentrations of EGFR and ErbB2, both members of the EGFR family, and future risk of glioma. Further, we studied if EGFR glioma risk variants were associated with EGFR and ErbB2 serum levels. We assessed the associations between genetic glioma risk variants and serum concentrations of EGFR and ErbB2, as measured in pre-diagnostic cohort serum samples of 593 glioma patients and 590 matched cancer-free controls. High serum EGFR and ErbB2 levels were associated with risk of developing glioblastoma (P = 0.008; OR = 1.58, 95 % CI = 1.13-2.22 and P = 0.017, OR = 1.63, 95 % CI = 1.09-2.44, respectively). High serum ErbB2 concentration was also associated with glioma risk overall (P = 0.049; OR = 1.39, 95 % CI = 1.00-1.93). Glioma risk variants were not associated with high serum protein abundance. In contrast, the EGFR risk variant rs4947986 (T) was correlated with decreased EGFR serum levels (study cohort P = 0.024 and controls P = 0.009). To our knowledge, this is the first study showing an association of EGFR and ErbB2 serum levels with glioma more than a decade before diagnosis, indicating that EGFR and ErbB2 serum proteins are important in early gliomagenesis. However, we did not find evidence that glioma risk variants were associated with high pre-diagnostic serum concentrations of EGFR and ErbB2., Competing Interests: Compliance with ethical standardsFundingThis study was supported by Acta Oncologica foundation through the Royal Swedish Academy of Science (BM salary), The Swedish Research Council, Swedish Cancer foundation, Northern Sweden Cancer foundation, Umeå University Young investigator reward, and Umeå Hospital cutting edge grant.Conflicts of interestNoneEthical approvalAll procedures involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Glioblastoma is associated with poor prognosis with a median survival of one year. High doses of ionizing radiation is the only established exogenous risk factor. To explore new potential biological risk factors for glioblastoma, we investigated alterations in metabolite concentrations in pre-diagnosed serum samples from glioblastoma patients diagnosed up to 22 years after sample collection, and undiseased controls. The study points out a latent biomarker for future glioblastoma consisting of nine metabolites (γ-tocopherol, α-tocopherol, erythritol, erythronic acid, myo-inositol, cystine, 2-keto-L-gluconic acid, hypoxanthine and xanthine) involved in antioxidant metabolism. We detected significantly higher serum concentrations of α-tocopherol (p=0.0018) and γ-tocopherol (p=0.0009) in future glioblastoma cases. Compared to their matched controls, the cases showed a significant average fold increase of α- and γ-tocopherol levels: 1.2 for α-T (p=0.018) and 1.6 for γ-T (p=0.003). These tocopherol levels were associated with a glioblastoma odds ratio of 1.7 (α-T, 95% CI:1.0-3.0) and 2.1 (γ-T, 95% CI:1.2-3.8). Our exploratory metabolomics study detected elevated serum levels of a panel of molecules with antioxidant properties as well as oxidative stress generated compounds. Additional studies are necessary to confirm the association between the observed serum metabolite pattern and future glioblastoma development., Competing Interests: The authors declare no conflicts of interest

During the last years, genome wide association studies have discovered common germline genetic variants associated with specific glioma subtypes. We aimed to study the association between these germline risk variants and tumor phenotypes, including copy number aberrations and protein expression. A total of 91 glioma patients were included. Thirteen well known genetic risk variants in TERT, EGFR, CCDC26, CDKN2A, CDKN2B, PHLDB1, TP53, and RTEL1 were selected for investigation of possible correlations with the glioma somatic markers: EGFR amplification, 1p/19q codeletion and protein expression of p53, Ki-67, and mutated IDH1. The CDKN2A/B risk variant, rs4977756, and the CDKN2B risk variant, rs1412829 were inversely associated (p = 0.049 and p = 0.002, respectively) with absence of a mutated IDH1, i.e., the majority of patients homozygous for the risk allele showed no or low expression of mutated IDH1. The RTEL1 risk variant, rs6010620 was associated (p = 0.013) with not having 1p/19q codeletion, i.e., the majority of patients homozygous for the risk allele did not show 1p/19q codeletion. In addition, the EGFR risk variant rs17172430 and the CDKN2B risk variant rs1412829, both showed a trend for association (p = 0.055 and p = 0.051, respectively) with increased EGFR copy number, i.e., the majority of patients homozygote for the risk alleles showed chromosomal gain or amplification of EGFR. Our findings indicate that CDKN2A/B risk genotypes are associated with primary glioblastoma without IDH mutation, and that there is an inverse association between RTEL1 risk genotypes and 1p/19q codeletion, suggesting that these genetic variants have a molecular impact on the genesis of high graded brain tumors. Further experimental studies are needed to delineate the functional mechanism of the association between genotype and somatic genetic aberrations.

Background: Glioblastomas progress rapidly making response evaluation using MRI insufficient since treatment effects are not detectable until months after initiation of treatment. Thus, there is a strong need for supplementary biomarkers that could provide reliable and early assessment of treatment efficacy. Analysis of alterations in the metabolome may be a source for identification of new biomarker patterns harboring predictive information. Ideally, the biomarkers should be found within an easily accessible compartment such as the blood., Method: Using gas-chromatographic- time-of-flight-mass spectroscopy we have analyzed serum samples from 11 patients with glioblastoma during the initial phase of radiotherapy. Fasting serum samples were collected at admittance, on the same day as, but before first treatment and in the morning after the second and fifth dose of radiation. The acquired data was analyzed and evaluated by chemometrics based bioinformatics methods. Our findings were compared and discussed in relation to previous data from microdialysis in tumor tissue, i.e. the extracellular compartment, from the same patients., Results: We found a significant change in metabolite pattern in serum comparing samples taken before radiotherapy to samples taken during early radiotherapy. In all, 68 metabolites were lowered in concentration following treatment while 16 metabolites were elevated in concentration. All detected and identified amino acids and fatty acids together with myo-inositol, creatinine, and urea were among the metabolites that decreased in concentration during treatment, while citric acid was among the metabolites that increased in concentration. Furthermore, when comparing results from the serum analysis with findings in tumor extracellular fluid we found a common change in metabolite patterns in both compartments on an individual patient level. On an individual metabolite level similar changes in ornithine, tyrosine and urea were detected. However, in serum, glutamine and glutamate were lowered after treatment while being elevated in the tumor extracellular fluid., Conclusion: Cross-validated multivariate statistical models verified that the serum metabolome was significantly changed in relation to radiation in a similar pattern to earlier findings in tumor tissue. However, all individual changes in tissue did not translate into changes in serum. Our study indicates that serum metabolomics could be of value to investigate as a potential marker for assessing early response to radiotherapy in malignant glioma.

The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF ≤ 1%) variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants, as well as rare, population-specific, coding variants. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal = 53,236) and fracture (ntotal = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD (rs11692564(T), MAF = 1.6%, replication effect size = +0.20 s.d., Pmeta = 2 × 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 × 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1(cre/flox) mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size = +0.41 s.d., Pmeta = 1 × 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.

Recent studies have described a number of genes that are frequently altered in medulloblastoma tumors and that have putative key roles in the development of the disease. We hypothesized that common germline genetic variations in these genes may be associated with medulloblastoma development. Based on recent publications, we selected 10 genes that were frequently altered in medulloblastoma: CCND2, CTNNB1, DDX3X, GLI2, SMARCA4, MYC, MYCN, PTCH1, TP53, and MLL2 (now renamed as KMT2D). Common genetic variants (single nucleotide polymorphisms) annotating these genes (n = 221) were genotyped in germline DNA (neonatal dried blood spot samples) from 243 childhood medulloblastoma cases and 247 control subjects from Sweden and Denmark. Eight genetic variants annotating three genes in the sonic hedgehog signaling pathway; CCND2, PTCH1, and GLI2, were found to be associated with the risk of medulloblastoma (P(combined) < 0.05). The findings were however not statistically significant following correction for multiple testing by the very stringent Bonferroni method. The results do not support our hypothesis that common germline genetic variants in the ten studied genes are associated with the risk of developing medulloblastoma.

Background: Although glioma etiology is poorly understood in general, growing evidence indicates a genetic component. Four large genome-wide association studies (GWAS) have linked common genetic variants with an increased glioma risk. However, to date, these studies are based largely on a case-control design, where cases have been recruited at the time of or after diagnosis. They may therefore suffer from a degree of survival bias, introduced when rapidly fatal cases are not included., Methods: To confirm glioma risk variants in a prospective setting, we have analyzed 11 previously identified risk variants in a set of prediagnostic serum samples with 598 cases and 595 matched controls. Serum samples were acquired from The Janus Serum Bank, a Norwegian population-based biobank reserved for cancer research., Results: We confirmed the association with glioma risk for variants within five genomic regions: 8q24.21 (CCDC26), 9p21.3 (CDKN2B-AS1), 11q23.3 (PHLDB1), 17p13.1 (TP53), and 20q13.33 (RTEL1). However, previously identified risk variants within the 7p11.2 (EGFR) region were not confirmed by this study., Conclusions: Our results indicate that the risk variants that were confirmed by this study are truly associated with glioma risk and may, consequently, affect gliomagenesis. Though the lack of positive confirmation of EGFR risk variants may be attributable to relatively limited statistical power, it nevertheless raises the question whether they truly are risk variants or markers for glioma prognosis., Impact: Our findings indicate the need for further studies to clarify the role of glioma risk loci with respect to prolonged survival versus etiology., (©2015 American Association for Cancer Research.)

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., (© The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Surface-enhanced laser desorption/ionization mass spectrometry (SELDI-MS) is an established, chip-based method for protein profiling, typically used for biomarker discovery. By combining retention chromatography and mass spectrometry on the same analytical platform, it allows for reliable analyses of small sample quantities in a high-throughput fashion. As such, it is a highly useful tool for a wide range of research fields. We have successfully applied it on brain tumor tissue samples to screen for differences in protein expression between invasive and noninvasive benign meningioma. This chapter lays out the details of the protocols we used, and can serve as a guide for protein expression profiling experiments on brain tumor tissue using SELDI-MS.

Background: The malignant brain tumour glioblastoma is a devastating disease that remains a therapeutic challenge., Materials and Methods: Effects of combinations of the US Food and Drug Administation (FDA) approved proteasome inhibitor bortezomib and the histone deacetylase (HDAC) inhibitors vorinostat, valproic acid and sodium phenylbutyrate were studied on primary glioblastoma stem cell lines and conventional glioblastoma cell lines. Cell survival, proliferation and death were analyzed by fluorometric microculture cytotoxicity assay (FMCA), propidium iodide labeling and flow cytometry, and cell cloning through limiting dilution and live-cell bright-field microscopy., Results: Bortezomib and the HDAC inhibitors showed synergistic cell killing at clinically relevant drug concentrations, while the conventional cell lines cultured in serum-containing medium were relatively resistant to the same treatments., Conclusion: These findings of synergistic glioblastoma stem cell killing by bortezomib and three different FDA-approved HDAC inhibitors confirm and expand previous observations on co-operative effects between these classes of drugs.

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.

A number of gene variants have been associated with an increased risk of developing glioma. We hypothesized that the reported risk variants may be associated with tumor genomic instability. To explore potential correlations between germline risk variants and somatic genetic events, we analyzed matched tumor and blood samples from 95 glioma patients by means of SNP genotyping. The generated genotype data was used to calculate genome-wide allele-specific copy number profiles of the tumor samples. We compared the copy number profiles across samples and found two EGFR gene variants (rs17172430 and rs11979158) that were associated with homozygous deletion at the CDKN2A/B locus. One of the EGFR variants (rs17172430) was also associated with loss of heterozygosity at the EGFR locus. Our findings were confirmed in a separate dataset consisting of matched blood and tumor samples from 300 glioblastoma patients, compiled from publically available TCGA data. These results imply there is a functional effect of germline EGFR variants on tumor progression.

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.

The treatment of glioblastoma is unsatisfactory. Improved understanding of the biological effects of treatment, together with development of new tools to predict outcome of the initiated treatment are therefore of great need. Vandetanib (ZD6474) is mainly a vascular endothelial growth factor (VEGF) and epidermal growth factor (EGF) receptor tyrosine kinase inhibitor. This study investigated the pattern of protein expression in brain tumor and normal brain tissue, following treatment with vandetanib in a rat glioma model. BT4C-cells were stereotactically implanted into the brain of BD IX rats. The rats were divided into three different experiments. The treatment schedule for experiments one and two consisted of daily, oral doses of vandetanib from day 6 until day 12 or 20 after implantation, respectively. In the third experiment, each animal received a single dose of vandetanib on day 19 after implantation and was then sacrificed 2, 8 or 24 h thereafter. The protein expression profiles were analyzed by SELDI-TOF-MS and evaluated with multivariate statistical methods. Following treatment with vandetanib, we found significantly altered protein expression pattern in malignant glioma and normal brain. Analyzing protein spectra is an interesting option to assess biological effects induced in brain tissue by signal transduction inhibitors such as vandetanib.

We employed stereotactic microdialysis to sample extracellular fluid intracranially from glioblastoma patients, before and during the first five days of conventional radiotherapy treatment. Microdialysis catheters were implanted in the contrast enhancing tumor as well as in the brain adjacent to tumor (BAT). Reference samples were collected subcutaneously from the patients' abdomen. The samples were analyzed by gas chromatography-time-of-flight mass spectrometry (GC-TOF MS), and the acquired data was processed by hierarchical multivariate curve resolution (H-MCR) and analyzed with orthogonal partial least-squares (OPLS). To enable detection of treatment-induced alterations, the data was processed by individual treatment over time (ITOT) normalization. One-hundred fifty-one metabolites were reliably detected, of which 67 were identified. We found distinct metabolic differences between the intracranially collected samples from tumor and the BAT region. There was also a marked difference between the intracranially and the subcutaneously collected samples. Furthermore, we observed systematic metabolic changes induced by radiotherapy treatment among both tumor and BAT samples. The metabolite patterns affected by treatment were different between tumor and BAT, both containing highly discriminating information, ROC values of 0.896 and 0.821, respectively. Our findings contribute to increased molecular knowledge of basic glioblastoma pathophysiology and point to the possibility of detecting metabolic marker patterns associated to early treatment response.

Meningiomas of WHO grade I can usually be cured by surgical resection. However, some tumors may, despite their benign appearance, display invasive growth behavior. These tumors constitute a difficult clinical problem to handle. By histology alone, bone invasive meningiomas may be indistinguishable from their noninvasive counterparts. In this study we have examined the protein spectra in a series of meningiomas in search of protein expression patterns that may distinguish between bone invasive and noninvasive meningiomas. Tumor tissue from 13 patients with fibrous (6 invasive and 7 noninvasive) and 29 with meningothelial (10 invasive and 19 noninvasive) grade I meningiomas were analyzed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI). Multivariate statistical methods were applied for data analyses. Comparing the protein spectra from invasive and noninvasive fibrous meningioma we found 22 peaks whose intensities were significantly different between the two groups (P < 0.001). Based on the expression pattern of these peaks we were able to perfectly separate the two entities (area under ROC curve = 1.0). In meningothelial meningioma the same comparison yielded six significantly differentially expressed peaks (P < 0.001), which to a large degree separated the invasive from noninvasive tissue (area under ROC curve = 0.873). By analyzing the protein spectra in benign meningiomas we could differentiate between invasive and noninvasive growth behavior in both fibrous and meningothelial meningiomas of grade I. A possibility for early identification of invasive grade I meningiomas may have a strong influence on the follow-up policy and the issue of early or late radiotherapy.

Papillomaviruses can roughly be divided into two tropism groups, those infecting the skin, including the genus beta PVs, and those infecting the mucosa, predominantly genus alpha PVs. The L1 capsid protein determines the phylogenetic separation between beta types and alpha types and the L1 protein is most probably responsible for the first interaction with the cell surface. Virus entry is a known determinant for tissue tropism and to study if interactions of the viral capsid with the cell surface could affect HPV tropism, the net surface charge of the HPV L1 capsid proteins was analyzed and HPV-16 (alpha) and HPV-5 (beta) with a mucosal and cutaneous tropism respectively were used to study heparin inhibition of uptake. The negatively charged L1 proteins were all found among HPVs with cutaneous tropism from the beta- and gamma-PV genus, while all alpha HPVs were positively charged at pH 7.4. The linear sequence of the HPV-5 L1 capsid protein had a predicted isoelectric point (pI) of 6.59 and a charge of -2.74 at pH 7.4, while HPV-16 had a pI of 7.95 with a charge of +2.98, suggesting no interaction between HPV-5 and the highly negative charged heparin. Furthermore, 3D-modelling indicated that HPV-5 L1 exposed more negatively charged amino acids than HPV-16. Uptake of HPV-5 (beta) and HPV-16 (alpha) was studied in vitro by using a pseudovirus (PsV) assay. Uptake of HPV-5 PsV was not inhibited by heparin in C33A cells and only minor inhibition was detected in HaCaT cells. HPV-16 PsV uptake was significantly more inhibited by heparin in both cells and completely blocked in C33A cells.

Many studies have suggested the hypothesis that the plasminogen activator (PA) system and the matrix metalloproteinase (MMP) system, either separately or in combination, may provide the proteolytic activity that is required for rupture of the follicular wall at the time of ovulation. Our recent studies on ovulation in plasminogen (plg)-deficient mice have, however, shown that plasmin is not required for normal ovulation, leading us to the hypothesis that MMPs may be a more important source of proteolysis for this process. To investigate the role of MMPs and also the possibility of a functional overlap or synergy between the MMP and PA systems during ovulation, we have studied ovulation efficiency in wild-type and plg-deficient mice treated with the broad-spectrum MMP inhibitor galardin. We found that in both wild-type mice and heterozygous plg-deficient (plg+/-) mice that had been treated with galardin prior to ovulation, there was a mild (18-20%) reduction in ovulation efficiency. Surprisingly, galardin treatment of plg-deficient (plg-/-) mice only caused an additional 14% reduction in ovulation efficiency as compared to vehicle-treated plg-/- mice. Our data therefore suggest that although MMPs may play a role in degradation of the follicular wall, they may not be obligatory for ovulation. In contrast to previous studies on tissue remodeling during wound healing and placental development, we have demonstrated that there is no obvious functional overlap or synergy between the PA and MMP systems, which has previously been thought to be essential for the ovulatory process.