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.
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.
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.
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.
CDKN2A/B; family history; glioma; MLH1; MSH2; TP53
The risk of glioma has consistently been shown to be increased two-fold 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 (Ptrend < 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.
Association; Polymorphisms; Glioma; Family history of primary brain tumor; Linkage analysis
Gliomas, which generally have a poor prognosis, are the most common primary malignant brain tumors in adults. Recent genome-wide association studies have demonstrated 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 SNPs, 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.
Glioma; family studies; linkage; haplotype pattern; NPL
Despite extensive research on the topic, glioma etiology remains largely unknown. Exploration of potential interactions between single-nucleotide polymorphisms (SNPs) of immune genes is a promising new area of glioma research. The case-only study design is a powerful and efficient design for exploring possible multiplicative interactions between factors that are independent of one another. The purpose of our study was to use this exploratory design to identify potential pair wise SNP-SNP interactions from genes involved in several different immune-related pathways for investigation in future studies.
The study population consisted of two case groups: 1224 histological-confirmed, non-Hispanic white glioma cases from the U.S. and a validation population of 634 glioma cases from the U.K. Polytomous logistic regression, in which one SNP was coded as the outcome and the other SNP was included as the exposure, was utilized to calculate the odds ratios of the likelihood of cases simultaneously having the variant alleles of two different SNPs. Potential interactions were examined only between SNPs located in different genes or chromosomes.
Using this data-mining strategy, we found 396 significant SNP-SNP interactions among polymorphisms of immune-related genes that were present in both the U.S. and U.K. study populations.
This exploratory study was conducted for the purpose of hypothesis generation, and thus has provided several new hypotheses that can be tested using traditional case-control study designs to obtain estimates of risk.
This is the first study, to our knowledge, to take this novel approach to identifying SNP-SNP interactions relevant to glioma etiology.
The value of hormone receptor and human epidermal growth factor receptor 2 expression for predicting overall survival, distant relapse, and locoregional relapse was examined in patients with inflammatory breast cancer. Triple-negative disease was associated with worse outcomes, indicating the need for developing new locoregional and systemic treatment strategies for patients with this aggressive subtype.
Numerous studies have demonstrated that expression of estrogen/progesterone receptor (ER/PR) and human epidermal growth factor receptor (HER)-2 is important for predicting overall survival (OS), distant relapse (DR), and locoregional relapse (LRR) in early and advanced breast cancer patients. However, these findings have not been confirmed for inflammatory breast cancer (IBC), which has different biological features than non-IBC.
We retrospectively analyzed the records of 316 women who presented to MD Anderson Cancer Center in 1989–2008 with newly diagnosed IBC without distant metastases. Most patients received neoadjuvant chemotherapy, mastectomy, and postmastectomy radiation. Patients were grouped according to receptor status: ER+ (ER+/PR+ and HER-2−; n = 105), ER+HER-2+ (ER+/PR+ and HER-2+; n = 37), HER-2+ (ER−/PR− and HER-2+; n = 83), or triple-negative (TN) (ER−PR−HER-2−; n = 91). Kaplan–Meier and Cox proportional hazards methods were used to assess LRR, DR, and OS rates and their associations with prognostic factors.
The median age was 50 years (range, 24–83 years). The median follow-up time and median OS time for all patients were both 33 months. The 5-year actuarial OS rates were 58.7% for the entire cohort, 69.7% for ER+ patients, 73.5% for ER+HER-2+ patients, 54.0% for HER=2+ patients, and 42.7% for TN patients (p < .0001); 5-year LRR rates were 20.3%, 8.0%, 12.6%, 22.6%, and 38.6%, respectively, for the four subgroups (p < .0001); and 5-year DR rates were 45.5%, 28.8%, 50.1%, 52.1%, and 56.7%, respectively (p < .001). OS and LRR rates were worse for TN patients than for any other subgroup (p < .0001–.03).
TN disease is associated with worse OS, DR, and LRR outcomes in IBC patients, indicating the need for developing new locoregional and systemic treatment strategies for patients with this aggressive subtype.
Inflammatory breast cancer; Estrogen receptor; Progesterone receptor; HER-2; Molecular subtypes
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.
family; glioma; meta-analysis; neoplasms
The etiology of brain tumors is still largely unknown. Previous research indicates that infectious agents and immunological characteristics may influence adult glioma risk. The purpose of our study was to evaluate the effects of birth order and sibship size (total number of siblings), as indicators of the timing and frequency of early life infections, on adult glioma risk using a population of 489 cases and 540 cancer-free controls from the Harris County Brain Tumor Study. Odds ratios for birth order and sibship size were calculated separately from multivariable logistic regression models, adjusting for sex, family history of cancer, education, and age. Each one-unit increase in birth order confers a 13% decreased risk of glioma development in adulthood (OR=0.87, 95% CI=0.79–0.97). However, sibship size was not significantly associated with adult glioma status (OR=0.97, 95% CI=0.91–1.04). Our study indicates that individuals who were more likely to develop common childhood infections at an earlier age (those with a higher birth order) may be more protected against developing glioma in adulthood. More biological and epidemiological research is warranted to clarify the exact mechanisms through which the timing of common childhood infections and the course of early life immune development affect gliomagenesis.
glioma; life-course epidemiology; infection; hygiene hypothesis; immune development
Single nucleotide polymorphisms (SNPs) in inflammation-related genes have previously been shown to alter risks of developing various cancers. However, the effects of such SNPs on glioma risk remain unclear. We used a multistrategic approach to elucidate the relationship between glioma risk, asthma/allergies, and 23 literature-based functional SNPs in 11 inflammation genes. Genotyping was conducted on 373 histologically confirmed adult glioma patients and 365 cancer-free controls from the Harris County Brain Tumor Study. Deviations from the Hardy–Weinberg equilibrium were assessed using the χ2-test, and Akaike's information criterion was used to determine the best genetic model for each SNP. Odds ratios (ORs) were calculated both for each SNP individually and for grouped analyses, examining the effects of the numbers of adverse alleles on glioma risk in participants with and without asthma. In the single-locus analysis of the 23 examined SNPs, 1 pro-inflammatory and 2 anti-inflammatory gene SNPs were significantly associated with glioma risk (COX2/PTGS2, rs20417 [OR = 1.41]; IL10, rs1800896 [OR = 1.57]; and IL13, rs20541 [OR = 0.39], respectively). When we examined the joint effects of the risk-conferring alleles of these 3 SNPs, we found a significant trend indicating that the risk increases as the number of adverse alleles increase (P = .005). Stratifying by asthma status, we found that this dose–response-like trend of increasing risk is only present among those without asthma/allergies (P < .0001). Our study indicates that polymorphisms in inflammation genes are associated with glioma susceptibility, especially when a history of asthma/allergies is absent.
allergy; asthma; glioma; inflammation
Previous studies have been inconclusive in estimating the risk of different cancer sites among close relatives of glioma patients; however, malignant melanoma has been consistently described.
We obtained family history information from 1,476 glioma patients under age 75 who registered at M.D. Anderson Cancer Center between June 1992 and June 2006. The number of observed cancers (N=1,001) among 8,746 first-degree relatives (FDRs) were compared to the number expected from age-, sex-, and calendar-year specific rates from the Surveillance, Epidemiology, and End Results Program using standardized incidence ratios (SIRs).
The overall SIR for any cancer was 1.21 (95% CI; 1.14 – 1.29). Among FDRs under 45 years, the overall SIR was 5.08 and for relatives >45 the overall SIR was 0.95. The SIRs were significantly elevated for brain tumors (2.14), melanoma (2.02), and sarcoma (3.83). We observed an excess of pancreatic cancer which was significantly higher only among mothers.
We observed an overall 21% increase in cancer among the FDRs of glioma patients, including excess cases of brain tumors and melanoma which could point to similar genetic contributions to these two malignancies. A large international linkage study is underway to examine potential genomic regions important for familial glioma.
aggregation; cancer; glioma; first-degree relatives
Previous literature provides some evidence that atopic diseases, IgE levels, and inflammatory gene polymorphisms may be associated with risk of glioblastoma. The purpose of this study was to investigate the affects of certain inflammatory gene single nucleotide polymorphisms (SNPs) on patient survival. Malignant gliomas are the most common type of primary brain tumor in adults, however, few prognostic factors have been identified.
Using 694 incident adult glioma cases identified between 2001 and 2006 in Harris County, Texas, we examined seven SNPs in the interleukin 4, interleukin 13, and interleukin 4-receptor (IL4R) genes. Cox proportional hazards regression was used to examine the association between the SNPs and overall and long-term survival, controlling for age at diagnosis, time between diagnosis and registration, extent of surgical resection, radiation therapy, and chemotherapy.
We found that among high-grade glioma cases, IL4R rs1805016 (TT vs. GT/GG) was significantly protective against mortality over time (HR: 0.59; 95% CI: 0.40–0.88). The IL4R rs1805016 and rs1805015 TT genotypes were both found to be significantly associated with survival beyond one year among high-grade glioma patients (HR: 0.44; 95% CI: 0.27–0.73 and HR: 0.63; 95% CI: 0.44–0.91, respectively). Furthermore, the IL4R haplotype analysis showed that SNPs in the IL4R gene may be interacting together to affect long-term survival among high-grade glioma cases.
These findings indicate that polymorphisms in inflammation pathway genes may play an important role in glioma survival. Further research on the effects of these polymorphisms on glioma prognosis is warranted.
glioma; survival; IL-4 receptor; inflammation
The analysis of alterations that may occur in nature when segments of
chromosomes are copied (known as copy number alterations) has been a focus of
research to identify genetic markers of cancer. One high-throughput technique
recently adopted is the use of molecular inversion probes (MIPs) to measure
probe copy number changes. The resulting data consist of high-dimensional copy
number profiles that can be used to ascertain probe-specific copy number
alterations in correlative studies with patient outcomes to guide risk
stratification and future treatment. We propose a novel Bayesian variable
selection method, the hierarchical structured variable selection (HSVS) method,
which accounts for the natural gene and probe-within-gene architecture to
identify important genes and probes associated with clinically relevant
outcomes. We propose the HSVS model for grouped variable selection, where
simultaneous selection of both groups and within-group variables is of interest.
The HSVS model utilizes a discrete mixture prior distribution for group
selection and group-specific Bayesian lasso hierarchies for variable selection
within groups. We provide methods for accounting for serial correlations within
groups that incorporate Bayesian fused lasso methods for within-group selection.
Through simulations we establish that our method results in lower model errors
than other methods when a natural grouping structure exists. We apply our method
to an MIP study of breast cancer and show that it identifies genes and probes
that are significantly associated with clinically relevant subtypes of breast
copy number alteration; hierarchical variable selection; lasso; MIP data; MCMC
It is generally accepted that glioma develops through accumulation of genetic alterations. We hypothesized that polymorphisms of candidate genes involved in the DNA repair pathways may contribute to susceptibility to glioma. To address this possibility, we conducted a study of 373 Caucasian glioma cases and 365 cancer-free Caucasian controls to assess associations between glioma risk and 18 functional SNPs in DNA repair genes. We evaluated potential gene-gene and gene-environment interactions using a multi-analytic strategy combining logistic regression, multifactor dimensionality reduction (MDR), and classification and regression tree (CART) approaches. In the single-locus analysis, six SNPs (ERCC1 3’ UTR, XRCC1 R399Q, APEX1 E148D, PARP1 A762V, MGMT F84L, and LIG1 5’UTR) showed a significant association with glioma risk. In the analysis of cumulative genetic risk of multiple SNPs, a significant gene-dosage effect was found for increased glioma risk with increasing numbers of adverse genotypes involving the above-mentioned six SNPs (P trend = 0.0004). Further, both the MDR and CART analyses identified MGMT F84L as the predominant risk factor for glioma, and revealed strong interactions among ionizing radiation (IR) exposure, PARP1 A762V, MGMT F84L and APEX1 E148D. Interestingly, the risk for glioma was dramatically increased in IR exposure individuals who had the wild-type genotypes of both MGMT F84L and PARP1 A762V [adjusted odds ratios (OR), 5.95; 95% confidence intervals (CI), 2.21–16.65]. Taken together, these results suggest that polymorphisms in DNA repair genes may act individually or together to contribute to glioma risk.
Epidemiologists in the Brain Tumor Epidemiology Consortium (BTEC) have prioritized areas for further research. Although many risk factors have been examined over the past several decades, there are few consistent findings possibly due to small sample sizes in individual studies and differences between studies in subjects, tumor types, and methods of classification. Individual studies have generally lacked sufficient sample size to examine interactions. A major priority based on available evidence and technologies includes expanding research in genetics and molecular epidemiology of brain tumors. BTEC has taken an active role in promoting understudied groups such as pediatric brain tumors, the etiology of rare glioma subtypes, such as oligodendroglioma, and meningioma, which not uncommon, has only recently been systematically registered in the US. There is also a pressing need to bring more researchers, especially junior investigators, to study brain tumor epidemiology. However, relatively poor funding for brain tumor research has made it difficult to encourage careers in this area. We review the group’s consensus on the current state of scientific findings and present a consensus on research priorities to identify the important areas the science should move to address.
Glioma; Meningioma; Epidemiology; Genetics
Meningioma is a disease with considerable morbidity and is more commonly diagnosed in females than in males. Hormonally related risk factors have long been postulated to be associated with meningioma risk, but no examination of these factors has been undertaken in males.
Subjects were male patients with intracranial meningioma (n = 456), ranging in age from 20 to 79 years, who were diagnosed among residents of the states of Connecticut, Massachusetts, and North Carolina, the San Francisco Bay Area, and 8 counties in Texas and matched controls (n = 452). Multivariate logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI) for the association between hormonal factors and meningioma risk in men.
Use of soy and tofu products was inversely associated with meningioma risk (OR 0.50 [95% CI 0.37–0.68]). Increased body mass index (BMI) appears to be associated with an approximately 2-fold increased risk of developing meningioma in men. No other single hormone–related exposure was found to be associated with meningioma risk, although the prevalence of exposure to factors such as orchiectomy and vasectomy was very low.
Estrogen-like exogenous exposures, such as soy and tofu, may be associated with reduced risk of meningioma in men. Endogenous estrogen–associated factors such as high BMI may increase risk. Examination of other exposures related to these factors may lead to better understanding of mechanisms and potentially to intervention.
Glioma is a rare, but highly fatal, cancer that accounts for the majority of malignant primary brain tumors. Inherited predisposition to glioma has been consistently observed within non-syndromic families. Our previous studies, which involved non-parametric and parametric linkage analyses, both yielded significant linkage peaks on chromosome 17q. Here, we use data from next generation and Sanger sequencing to identify familial glioma candidate genes and variants on chromosome 17q for further investigation. We applied a filtering schema to narrow the original list of 4830 annotated variants down to 21 very rare (<0.1% frequency), non-synonymous variants. Our findings implicate the MYO19 and KIF18B genes and rare variants in SPAG9 and RUNDC1 as candidates worthy of further investigation. Burden testing and functional studies are planned.
To identify and validate copy number aberrations in early-stage primary breast tumors associated with bone or non-bone metastasis.
Patients and Methods
Whole-genome molecular inversion probe arrays were used to evaluate copy number imbalances (CNIs) in breast tumors from 960 early-stage patients with information about site of metastasis. The CoxBoost algorithm was used to select metastasis site-related CNIs and to fit a Cox proportional hazards model.
Gains at 1q41 and 1q42.12 and losses at 1p13.3, 8p22, and Xp11.3 were significantly associated with bone metastasis. Gains at 2p11.2, 3q21.3–22.2, 3q27.1, 10q23.1, and 14q13.2–3 and loss at 7q21.11 were associated with non-bone metastasis. To examine the joint effect of CNIs and clinical predictors, patients were stratified into three risk groups (low, intermediate, and high) based on the sum of predicted linear hazard ratios (HRs). For bone metastasis, the hazard (95% confidence interval) for the low-risk group was 0.32 (0.11–0.92) compared to the intermediate-risk group and 2.99 (1.74–5.11) for the high-risk group. For non-bone metastasis, the hazard for the low-risk group was 0.34 (0.17–0.66) and 2.33 (1.59–3.43) for the high-risk group. The prognostic value of loss at 8p22 for bone metastasis and gains at 10q23.1 for non-bone metastasis, and gain at 11q13.5 for both bone and non-bone metastases were externally validated in 335 breast tumors pooled from four independent cohorts.
Distinct CNIs are independently associated with bone and non-bone metastasis for early-stage breast cancer patients across cohorts. These data warrant consideration for tailoring surveillance and management of metastasis risk.
Breast cancer; bone metastasis; non-bone metastasis; copy number imbalances; molecular inversion probe array
An inverse association between personal history of allergies/asthma and glioma risk has been fairly consistently reported in the epidemiologic literature. However, the role of regular antihistamine use remains controversial due to a small number of studies reporting contradictory findings. We evaluated the association between regular use of oral antihistamines and glioma risk, adjusting for a number of relevant factors (e.g., immunoglobulin E levels and history of chickenpox).
We used a subset of the Harris County Case-Control Study, which included 362 pathologically-confirmed glioma cases and 462 cancer-free controls, to evaluate this association using unconditional multivariable logistic regression. These models were run among the overall study population and stratified by allergy status. Cox regression was utilized to examine whether antihistamine use was associated with mortality among all cases and separately among high-grade cases.
Antihistamine use was strongly associated with glioma risk among those with a positive allergy/asthma history (OR: 4.19, 95% CI: 2.06–8.51), but not among those with a negative history (OR: 1.59, 95% CI: 0.95–2.67). There were no significant associations between antihistamine use and survival among cases.
The current study implies that regular antihistamine use may increase glioma risk. However, several larger studies are necessary before definitive conclusions can be drawn.
brain neoplasms; risk factors; epidemiology; survival; case-control studies; hypersensitivity; immunoglobulin E
Acute leukemia is the most common cancer in children under 15 years of age; 80%
are acute lymphoblastic leukemia (ALL) and 17% are acute myeloid leukemia (AML). Childhood
leukemia shows further diversity based on cytogenetic and molecular characteristics, which may
relate to distinct etiologies. Case–control studies conducted worldwide, particularly of
ALL, have collected a wealth of data on potential risk factors and in some studies, biospecimens.
There is growing evidence for the role of infectious/immunologic factors, fetal growth, and several
environmental factors in the etiology of childhood ALL. The risk of childhood leukemia, like other
complex diseases, is likely to be influenced both by independent and interactive effects of genes
and environmental exposures. While some studies have analyzed the role of genetic variants, few have
been sufficiently powered to investigate gene–environment interactions.
The Childhood Leukemia International Consortium (CLIC) was established in 2007 to promote
investigations of rarer exposures, gene–environment interactions and subtype-specific
associations through the pooling of data from independent studies.
By September 2012, CLIC included 22 studies (recruitment period: 1962–present)
from 12 countries, totaling approximately 31 000 cases and 50 000 controls. Of these, 19
case–control studies have collected detailed epidemiologic data, and DNA samples have been
collected from children and child–parent trios in 15 and 13 of these studies, respectively.
Two registry-based studies and one study comprising hospital records routinely obtained at birth
and/or diagnosis have limited interview data or biospecimens.
CLIC provides a unique opportunity to fill gaps in knowledge about the role of
environmental and genetic risk factors, critical windows of exposure, the effects of
gene–environment interactions and associations among specific leukemia subtypes in different
Leukemia; Children; Consortium; Epidemiology; Genetics
Familial cancer can be used to leverage genetic association studies. Recent genome-wide association studies have reported independent associations between seven single nucleotide polymorphisms (SNPs) and risk of glioma. The aim of this study was to investigate whether glioma cases with a positive family history of brain tumours, defined as having at least one first or second degree relative with a history of brain tumour, are associated with known glioma risk loci. 1431 glioma cases and 2868 cancer-free controls were identified from four case-control studies and two prospective cohorts from USA, Sweden, and Denmark and genotyped for seven SNPs previously reported to be associated with glioma risk in case-control designed studies. Odds ratios were calculated by unconditional logistic regression. In analyses including glioma cases with a family history of brain tumours (n=104) and control subjects free of glioma at baseline, three out of seven SNPs were associated with glioma risk; rs2736100 (5p15.33, TERT), rs4977756 (9p21.3, CDKN2A-CDKN2B), and rs6010620 (20q13.33, RTEL1). After Bonferroni correction for multiple comparisons, only one marker was statistically significantly associated with glioma risk, rs6010620 (ORtrend for the minor (A) allele, 0.39; 95% CI, 0.25–0.61; Bonferroni adjusted ptrend, 1.7×10−4). In conclusion, as previously shown for glioma regardless of family history of brain tumours, rs6010620 (RTEL1) was associated with an increased risk of glioma when restricting to cases with family history of brain tumours. These findings require confirmation in further studies with a larger number of glioma cases with a family history of brain tumours.
Glioma; brain tumours; genome-wide association study; single nucleotide polymorphism
We recently identified a pivotal role for the host type I interferon (IFN) pathway in immuno-surveillance against de novo mouse glioma development, especially through the regulation of immature myeloid cells (IMCs) in the glioma microenvironment. Using these data, we identified single nucleotide polymorphisms (SNPs) in human IFN genes that dictate altered prognosis of patients with glioma. One of these SNPs (rs12553612) is located in the promoter of IFNA8, whose promoter activity is influenced by rs12553612. Conversely, recent epidemiologic data show that chronic usage of non-steroidal anti-inflammatory drugs lowers the risk of glioma. We translated these findings back to our de novo glioma model and found that cyclooxygenase-2 inhibition enhances anti-glioma immuno-surveillance by reducing glioma-associated IMCs. Taken together, these findings suggest that alterations in myeloid cell function condition the brain for glioma development. Finally, we have begun applying novel immunotherapeutic approaches to patients with low-grade glioma with the aim of preventing malignant transformation. Future research will hopefully better integrate epidemiological, immunobiological, and translational techniques to develop novel preventive approaches for malignant gliomas.
interferon; glioma; non-steroidal anti-inflammatory drugs; single nucleotide polymorphism
Several single-nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified through genome-wide association studies. This study investigated the association of eight risk SNPs with breast cancer disease-free survival and overall survival rates. Results suggest that two previously identified breast cancer risk susceptibility loci may influence breast cancer prognosis or comorbid conditions associated with overall survival.
Describe the results of genome-wide association studies (GWAS) that have identified genetic variants associated with breast cancer risk.Discuss whether genetic risk variants identified through genome-wide association studies (GWAS) are also associated with breast cancer prognosis.Describe molecular mechanisms through which germline genetic variants may influence breast cancer survival.
Several single-nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified through genome-wide association studies (GWAS). We investigated whether eight risk SNPs identified in GWAS were associated with breast cancer disease-free survival (DFS) and overall survival (OS) rates.
Patients and Methods.
A cohort of 739 white women with early-stage breast cancer was genotyped for eight GWAS-identified SNPs (rs2981582, rs1219648 [FGFR2], rs3803662, rs12443621, rs8051542 [TOX3], rs999737 [RAD51L1], rs6504950 [17q23], and rs4973768 [3p24]). Relationships between SNPs and breast cancer outcomes were evaluated using Cox proportional hazard regression models. The cumulative effects of SNPs on breast cancer outcomes were assessed by computing the number of at-risk genotypes.
At a median follow-up of 121 months (range: 188–231 months) for survivors, 237 deaths (32%) and 186 breast cancer events (25%) were identified among the 739 patients. After adjusting for age, clinical stage, and treatment, rs12443621 (16q12; p = .03) and rs6504950 (17q23; p = .008) were prognostic for OS but not DFS. A higher risk for death was also found in the multivariable analysis of patients harboring three or four at-risk genotypes of the GWAS SNPs compared to patients carrying two or less at-risk genotypes (hazard ratio: 1.60, 95% confidence interval: 1.23–2.24; p = .0008).
The study results suggest that previously identified breast cancer risk susceptibility loci, rs12443621 (16q12) and rs6504950 (17q23), may influence breast cancer prognosis or comorbid conditions associated with overall survival. The precise molecular mechanisms through which these risk SNPs, as well as others that were not included in the analysis, influence clinical outcomes remain to be determined.
Breast cancer; Prognosis; Single-nucleotide polymorphisms; TNRC9; 17q23
While certain inherited syndromes (e.g. Neurofibromatosis or Li-Fraumeni) are associated with an increased risk of glioma, most familial gliomas are non-syndromic. This study describes the demographic and clinical characteristics of the largest series of non-syndromic glioma families ascertained from 14 centres in the United States (US), Europe and Israel as part of the Gliogene Consortium.
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.
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.
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.
Glioma; Familial glioma; Clinical characteristics; Genetic counselling
To examine the role of germline genetic variations in inflammatory pathways as modifiers of time to recurrence (TTR) in patients with early stage breast cancer (BC), DNA from 997 early stage BC patients was genotyped for 53 tagging single nucleotide polymorphisms (SNPs) in 12 genes involved in inflammation. SNPs were analyzed separately for Caucasians versus African Americans and Hispanics. Cox proportional hazards models were used to evaluate the association between SNPs in the inflammatory genes and time to recurrence (TTR), adjusted for clinical and pathologic covariates. In univariable analyses of Caucasian women, the homozygous genotype of 12 SNPs, including 6 NFKB1 SNPs, 4 IL4 SNPs, and 2 IL13 SNPs, were significantly associated with a decrease in TTR compared with the heterozygous and/ or corresponding homozygous genotype (P <0.05). The significant NFKB1 and IL4 SNPs were in an area of high linkage disequilibrium (D'>0.8). After adjusting for stage, age, and treatment, carriage of the homozygous genotypes for NFKB1rs230532 and IL13rs1800925 were independently associated with a shorter TTR (P=0.001 and p=0.034, respectively). In African-American and Hispanic patients, expression of NFKB1rs3774932, TNFrs1799964, and IL4rs3024543 SNPs were associated with a shorter TTR in univariable model. Only NFKB1 rs3774932 (P=0.02) and IL4Rrs3024543 (P=0.03) had independent prognostic value in the multivariable model These data support the existence of host genetic susceptibility as a component in recurrence risk mediated by pro-inflammatory and immune factors, and suggest the potential for drugs which modify immune responses and inflammatory genes to improve prognosis in early stage BC.
gene polymorphisms; inflammation; breast cancer
Self-rated health (SRH), a consistent predictor of mortality among diverse populations, is sensitive to health indicators and social factors. American-born Hispanics report better SRH than their foreign-born counterparts but simultaneously report poorer health indicators and have shorter life expectancy. Using a matched prospective cross-sectional design, we analyzed data from 631 age-matched pairs of women, born in the United States or Mexico, enrolled in a cohort study based in Houston, Texas. Our first goal was to describe the relationships between SRH and health behaviors, physician-diagnosed chronic conditions, acculturation, and socioeconomic status (SES) by birthplace. Our second goal was to investigate the relative influence of SES, acculturation, health behaviors, and physician-diagnosed conditions in explaining expected differences in SRH between the two groups. Number of chronic conditions reported, particularly depression, more strongly influenced SRH than SES, acculturation, or reported health risk behaviors and the influence of birthplace is accounted for by these factors.
Self-rated health; acculturation; SES; health indicators