1. |
- Liu, Yanhong, et al.
(author)
-
Polymorphisms of LIG4, BTBD2, HMGA2, and RTEL1 genes involved in the double-strand break repair pathway predict glioblastoma survival
- 2010
-
In: Journal of Clinical Oncology. - : American Society of Clinical Oncology. - 0732-183X .- 1527-7755. ; 28:14, s. 2467-2474
-
Journal article (peer-reviewed)abstract
- 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= 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.
|
|
2. |
|
|
3. |
- Andersson, Ulrika, et al.
(author)
-
Germline rearrangements in families with strong family history of glioma and malignant melanoma, colon, and breast cancer
- 2014
-
In: Neuro-Oncology. - : Oxford University Press. - 1522-8517 .- 1523-5866. ; 16:10, s. 1333-1340
-
Journal article (peer-reviewed)abstract
- 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.
|
|
4. |
|
|
5. |
- Enciso-Mora, Victor, et al.
(author)
-
Deciphering the 8q24.21 association for glioma
- 2013
-
In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 22:11, s. 2293-2302
-
Journal article (peer-reviewed)abstract
- We have previously identified tagSNPs at 8q24.21 influencing glioma risk. We have sought to fine-map the location of the functional basis of this association using data from four genome-wide association studies, comprising a total of 4147 glioma cases and 7435 controls. To improve marker density across the 700 kb region, we imputed genotypes using 1000 Genomes Project data and high-coverage sequencing data generated on 253 individuals. Analysis revealed an imputed low-frequency SNP rs55705857 (P = 2.24 x 10(-38)) which was sufficient to fully capture the 8q24.21 association. Analysis by glioma subtype showed the association with rs55705857 confined to non-glioblastoma multiforme (non-GBM) tumours (P = 1.07 x 10(-67)). Validation of the non-GBM association was shown in three additional datasets (625 non-GBM cases, 2412 controls; P = 1.41 x 10(-28)). In the pooled analysis, the odds ratio for low-grade glioma associated with rs55705857 was 4.3 (P = 2.31 x 10(-94)). rs55705857 maps to a highly evolutionarily conserved sequence within the long non-coding RNA CCDC26 raising the possibility of direct functionality. These data provide additional insights into the aetiological basis of glioma development.
|
|
6. |
|
|
7. |
|
|
8. |
- Liu, Yanhong, et al.
(author)
-
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
- 2012
-
In: Human Genetics. - : Springer Science and Business Media LLC. - 0340-6717 .- 1432-1203. ; 131:9, s. 1507-1517
-
Journal article (peer-reviewed)abstract
- 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.
|
|
9. |
- Robertson, Lindsay B, et al.
(author)
-
Survey of familial glioma and role of germline p16INK4A/p14ARF and p53 mutation
- 2010
-
In: Familial Cancer. - : Springer Science and Business Media LLC. - 1389-9600 .- 1573-7292. ; 9:3, s. 413-421
-
Journal article (peer-reviewed)abstract
- There is increasing recognition of familial propensity to glioma as a distinct clinical entity beyond a few rare syndromes; however its genetic basis is poorly understood. The role of p16(INK4A)/p14(ARF) and p53 mutations in sporadic glioma provides a strong rationale for investigating germline mutations in these genes as a cause of familial glioma. To survey the familial glioma phenotype and examine the contribution of germline mutation in p16(INK4A)/p14(ARF) and p53 to the disease we have analyzed a series of 101 index familial cases collected through the GLIOGENE Consortium (http://braintumor.epigenetic.org/). There was little evidence for within family correlations for tumour histology, suggesting generic susceptibility to glial tumors. We did not detect any functional mutations in p16(INK4A) or p14(ARF). One index case with glioblastoma multiforme (GBM) diagnosed at age 54 and had a family history comprised of a paternal aunt with GBM at age 55, carried the p53 R158H mutation, which is predicted to be functional and has previously been implicated as a cause of Li-Fraumeni syndrome. Our findings provide no evidence that p16(INK4A)/p14(ARF) and p53 mutations contribute significantly to familial glioma.
|
|
10. |
- Sadetzki, Siegal, et al.
(author)
-
Description of selected characteristics of familial glioma patients : Results from the Gliogene Consortium
- 2013
-
In: European Journal of Cancer. - : Elsevier. - 0959-8049 .- 1879-0852. ; 49:6, s. 1335-1345
-
Journal article (peer-reviewed)abstract
- Background: While certain inherited syndromes (e. g. Neurofibromatosis or LiFraumeni) are associated with an increased risk of glioma, most familial gliomas are nonsyndromic. 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 < 40 y, and in 12% both were diagnosed under 40 y 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 17 y 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. (C) 2012 Elsevier Ltd. All rights reserved.
|
|
11. |
- Shete, Sanjay, et al.
(author)
-
Genome-wide high-density SNP linkage search for glioma susceptibility loci : results from the gliogene consortium
- 2011
-
In: Cancer Research. - 0008-5472 .- 1538-7445. ; 71:24, s. 7568-7575
-
Journal article (peer-reviewed)abstract
- 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. Cancer Res; 71(24); 7568-75. (C) 2011 AACR.
|
|
12. |
- Sun, Xiangqing, et al.
(author)
-
A variable age of onset segregation model for linkage analysis, with correction for ascertainment, applied to glioma
- 2012
-
In: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 21:12, s. 2242-2251
-
Journal article (peer-reviewed)abstract
- Background: We propose a two-step model-based approach, with correction for ascertainment, to linkage analysis of a binary trait with variable age of onset and apply it to a set of multiplex pedigrees segregating for adult glioma.Methods: First, we fit segregation models by formulating the likelihood for a person to have a bivariate phenotype, affection status and age of onset, along with other covariates, and from these we estimate population trait allele frequencies and penetrance parameters as a function of age (N=281 multiplex glioma pedigrees). Second, the best fitting models are used as trait models in multipoint linkage analysis (N=74 informative multiplex glioma pedigrees). To correct for ascertainment, a prevalence constraint is used in the likelihood of the segregation models for all 281 pedigrees. Then the trait allele frequencies are re-estimated for the pedigree founders of the subset of 74 pedigrees chosen for linkage analysis.Results: Using the best fitting segregation models in model-based multipoint linkage analysis, we identified two separate peaks on chromosome 17; the first agreed with a region identified by Shete et al. (1) who used model-free affected-only linkage analysis, but with a narrowed peak: and the second agreed with a second region they found but had a larger maximum LOD.Conclusions/Impact: Our approach has the advantage of not requiring markers to be in linkage equilibrium unless the minor allele frequency is small (markers which tend to be uninformative for linkage), and of using more of the available information for LOD-based linkage analysis.
|
|