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1.  Single nucleotide polymorphisms in nucleotide excision repair genes, cancer treatment, and head and neck cancer survival 
Cancer causes & control : CCC  2014;25(4):437-450.
Head and neck cancers (HNC) are commonly treated with radiation and platinum-based chemotherapy, which produce bulky DNA adducts to eradicate cancerous cells. Because nucleotide excision repair (NER) enzymes remove adducts, variants in NER genes may be associated with survival among HNC cases both independently and jointly with treatment.
Cox proportional hazards models were used to estimate race-stratified (White, African American) hazard ratios (HRs) and 95 % confidence intervals for overall (OS) and disease-specific (DS) survival based on treatment (combinations of surgery, radiation, and chemotherapy) and 84 single nucleotide polymorphisms (SNPs) in 15 NER genes among 1,227 HNC cases from the Carolina Head and Neck Cancer Epidemiology Study.
None of the NER variants evaluated were associated with survival at a Bonferroni-corrected alpha of 0.0006. However, rs3136038 [OS HR = 0.79 (0.65, 0.97), DS HR = 0.69 (0.51, 0.93)] and rs3136130 [OS HR = 0.78 (0.64, 0.96), DS HR = 0.68 (0.50, 0.92)] of ERCC4 and rs50871 [OS HR = 0.80 (0.64, 1.00), DS HR = 0.67 (0.48, 0.92)] of ERCC2 among Whites, and rs2607755 [OS HR = 0.62 (0.45, 0.86), DS HR = 0.51 (0.30, 0.86)] of XPC among African Americans were suggestively associated with survival at an uncorrected alpha of 0.05. Three SNP-treatment joint effects showed possible departures from additivity among Whites.
Our study, a large and extensive evaluation of SNPs in NER genes and HNC survival, identified mostly null associations, though a few variants were suggestively associated with survival and potentially interacted additively with treatment.
PMCID: PMC4096829  PMID: 24487794
Head and neck cancer DNA repair; Nucleotide excision repair; Chemotherapy; Radiation; Survival
2.  Description of selected characteristics of familial glioma patients – Results from the Gliogene Consortium 
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.
PMCID: PMC3615132  PMID: 23290425
Glioma; Familial glioma; Clinical characteristics; Genetic counselling
3.  Risk of subsequent cancer following a primary CNS tumor 
Journal of neuro-oncology  2013;112(2):285-295.
Improvements in survival among central nervous system (CNS) tumor patients has made the risk of developing a subsequent cancer an important survivorship issue. Such a risk is likely influenced by histological and treatment differences between CNS tumors. De-identified data for 41,159 patients with a primary CNS tumor diagnosis from 9 Surveillance, Epidemiology and End Results (SEER) registries were used to calculate potential risk for subsequent cancer development. Relative risk (RR) and 95 % confidence interval (CI) of subsequent cancer was calculated using SEER*Stat 7.0.9, comparing observed number of subsequent cancers versus expected in the general United States population. For all CNS tumors studied, there were 830 subsequent cancers with a RR of 1.26 (95 % CI, 1.18–1.35). Subsequent cancers were observed in the CNS, digestive system, bones/joints, soft tissue, thyroid and leukemia. Radiotherapy was associated with an elevated risk, particularly in patients diagnosed with a medulloblastoma/primitive neuroectodermal tumor (MPNET). MPNET patients who received radiotherapy were at a significant risk for development of cancers of the digestive system, leukemia, bone/joint and cranial nerves. Glioblastoma multiforme patients who received radiotherapy were at lower risks for female breast and prostate cancers, though at an elevated risk for cancers of the thyroid and brain. Radiotherapy is associated with subsequent cancer development, particularly for sites within the field of radiation, though host susceptibility and post-treatment status underlie this risk. Variation in subsequent cancer risk among different CNS tumor histological subtypes indicate a complex interplay between risk factors in subsequent cancer development.
PMCID: PMC3777246  PMID: 23392847
Central nervous system cancer; Subsequent cancer; Radiotherapy; Surveillance, Epidemiology and End Results (SEER) Program
4.  Molecular Subtypes of Glioblastoma Are Relevant to Lower Grade Glioma 
PLoS ONE  2014;9(3):e91216.
Gliomas are the most common primary malignant brain tumors in adults with great heterogeneity in histopathology and clinical course. The intent was to evaluate the relevance of known glioblastoma (GBM) expression and methylation based subtypes to grade II and III gliomas (ie. lower grade gliomas).
Gene expression array, single nucleotide polymorphism (SNP) array and clinical data were obtained for 228 GBMs and 176 grade II/II gliomas (GII/III) from the publically available Rembrandt dataset. Two additional datasets with IDH1 mutation status were utilized as validation datasets (one publicly available dataset and one newly generated dataset from MD Anderson). Unsupervised clustering was performed and compared to gene expression subtypes assigned using the Verhaak et al 840-gene classifier. The glioma-CpG Island Methylator Phenotype (G-CIMP) was assigned using prediction models by Fine et al.
Unsupervised clustering by gene expression aligned with the Verhaak 840-gene subtype group assignments. GII/IIIs were preferentially assigned to the proneural subtype with IDH1 mutation and G-CIMP. GBMs were evenly distributed among the four subtypes. Proneural, IDH1 mutant, G-CIMP GII/III s had significantly better survival than other molecular subtypes. Only 6% of GBMs were proneural and had either IDH1 mutation or G-CIMP but these tumors had significantly better survival than other GBMs. Copy number changes in chromosomes 1p and 19q were associated with GII/IIIs, while these changes in CDKN2A, PTEN and EGFR were more commonly associated with GBMs.
GBM gene-expression and methylation based subtypes are relevant for GII/III s and associate with overall survival differences. A better understanding of the association between these subtypes and GII/IIIs could further knowledge regarding prognosis and mechanisms of glioma progression.
PMCID: PMC3948818  PMID: 24614622
5.  Somatic alterations in brain tumors 
Oncology reports  2008;20(1):203-210.
Mutations in TP53 and RB1 have been shown to participate in the development of malignant brain tumors. Emerging evidence shows that mutations are involved in LGI1 in brain tumor progression. Herein we present data from the sequencing of a series of high- and low-grade gliomas with matched normal DNA. We report on 35 unique missense mutations in TP53, RB1 and LGI1 genes and use available information for each mutation in order to classify them as likely to be ‘driver’ or ‘passenger’ mutations. The identification of putatively deleterious mutations in LGI1 supports the notion that this locus may play a role in brain cancer development.
PMCID: PMC3933973  PMID: 18575738
TP53; RB1; LGI1; glioblastoma; brain tumors; mutation analysis
6.  Genome-Wide Methylation Analyses in Glioblastoma Multiforme 
PLoS ONE  2014;9(2):e89376.
Few studies had investigated genome-wide methylation in glioblastoma multiforme (GBM). Our goals were to study differential methylation across the genome in gene promoters using an array-based method, as well as repetitive elements using surrogate global methylation markers. The discovery sample set for this study consisted of 54 GBM from Columbia University and Case Western Reserve University, and 24 brain controls from the New York Brain Bank. We assembled a validation dataset using methylation data of 162 TCGA GBM and 140 brain controls from dbGAP. HumanMethylation27 Analysis Bead-Chips (Illumina) were used to interrogate 26,486 informative CpG sites in both the discovery and validation datasets. Global methylation levels were assessed by analysis of L1 retrotransposon (LINE1), 5 methyl-deoxycytidine (5m-dC) and 5 hydroxylmethyl-deoxycytidine (5hm-dC) in the discovery dataset. We validated a total of 1548 CpG sites (1307 genes) that were differentially methylated in GBM compared to controls. There were more than twice as many hypomethylated genes as hypermethylated ones. Both the discovery and validation datasets found 5 tumor methylation classes. Pathway analyses showed that the top ten pathways in hypomethylated genes were all related to functions of innate and acquired immunities. Among hypermethylated pathways, transcriptional regulatory network in embryonic stem cells was the most significant. In the study of global methylation markers, 5m-dC level was the best discriminant among methylation classes, whereas in survival analyses, high level of LINE1 methylation was an independent, favorable prognostic factor in the discovery dataset. Based on a pathway approach, hypermethylation in genes that control stem cell differentiation were significant, poor prognostic factors of overall survival in both the discovery and validation datasets. Approaches that targeted these methylated genes may be a future therapeutic goal.
PMCID: PMC3931727  PMID: 24586730
7.  The tumor suppressor CDKN3 controls mitosis 
The Journal of Cell Biology  2013;201(7):997-1012.
A genome-wide screen of phosphatases that control mitosis identified CDKN3, which acts through the CDC2 signaling axis.
Mitosis is controlled by a network of kinases and phosphatases. We screened a library of small interfering RNAs against a genome-wide set of phosphatases to comprehensively evaluate the role of human phosphatases in mitosis. We found four candidate spindle checkpoint phosphatases, including the tumor suppressor CDKN3. We show that CDKN3 is essential for normal mitosis and G1/S transition. We demonstrate that subcellular localization of CDKN3 changes throughout the cell cycle. We show that CDKN3 dephosphorylates threonine-161 of CDC2 during mitotic exit and we visualize CDC2pThr-161 at kinetochores and centrosomes in early mitosis. We performed a phosphokinome-wide mass spectrometry screen to find effectors of the CDKN3-CDC2 signaling axis. We found that one of the identified downstream phosphotargets, CKβ phosphorylated at serine 209, localizes to mitotic centrosomes and controls the spindle checkpoint. Finally, we show that CDKN3 protein is down-regulated in brain tumors. Our findings indicate that CDKN3 controls mitosis through the CDC2 signaling axis. These results have implications for targeted anticancer therapeutics.
PMCID: PMC3691455  PMID: 23775190
8.  Expression of the Alpha Tocopherol Transfer Protein gene is regulated by Oxidative Stress and Common Single Nucleotide Polymorphisms 
Free radical biology & medicine  2012;53(12):10.1016/j.freeradbiomed.2012.10.528.
Vitamin E (α-tocopherol) is the major lipid soluble antioxidant in most animal species. By controlling the secretion of vitamin E from the liver, the α-tocopherol transfer protein (αTTP) regulates whole-body distribution and levels of this vital nutrient. However, the mechanism(s) that regulate the expression of this protein are poorly understood. Here we report that transcription of the TTPA gene in immortalized human hepatocytes (IHH) is induced by oxidative stress and by hypoxia, by agonists of the nuclear receptors PPARα and RXR, and by increased cAMP levels. The data show further that induction of TTPA transcription by oxidative stress is mediated by an already-present transcription factor, and does not require de novo protein synthesis. Silencing of the cAMP response element binding (CREB) transcription factor attenuated transcriptional responses of the TTPA gene to added peroxide, suggesting that CREB mediates responses of this gene to oxidative stress. Using a 1.9 Kb proximal segment of the human TTPA promoter together with site-directed mutagenesis approach, we found that single nucleotide polymorphisms (SNPs) that are commonly found in healthy humans dramatically affect promoter activity. These observations suggest that oxidative stress and individual genetic makeup contribute to vitamin E homeostasis in humans. These findings may explain the variable responses to vitamin E supplementation observed in human clinical trials.
PMCID: PMC3612136  PMID: 23079030
tocopherol; oxidative stress; single nucleotide polymorphism
9.  A variable age of onset segregation model for linkage analysis, with correction for ascertainment, applied to glioma 
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.
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.
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. 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 log of the odds (LOD).
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.
PMCID: PMC3518573  PMID: 22962404
Glioma; model-based linkage; segregation; age of onset; prevalence constraint
10.  Adiposity, inflammation, genetic variants and risk of post-menopausal breast cancer findings from a prospective-specimen-collection, retrospective-blinded-evaluation (PRoBE) design approach 
SpringerPlus  2013;2:638.
Chronic internal inflammation secondary to adiposity is a risk factor for sporadic breast cancer and Post-Menopausal Breast Cancer (PMBC) is largely defined as such. Adiposity is one of the clinical criteria for the diagnosis of Metabolic Syndrome (MetS) and is a risk factor for PMBC. We examined SNPs of eight genes implicated in adiposity, inflammation and cell proliferation in a Prospective-specimen-collection, Retrospective-Blinded-Evaluation (PRoBE) design approach. A total of 180 cases and 732 age-matched controls were identified from the MyCode prospective biobank database and then linked to the Clinical Decision Information System, an enterprise-wide data warehouse, to retrieve clinico-demographic data. Samples were analyzed in a core laboratory where the personnel were masked to their status. Results from multivariate logistic regression yielded one SNP (rs2922126) in the GHSR as protective against PMBC among homozygotes for the minor allele (A/A) (OR = 0.4, 95% CI 0.18-.89, P-value = .02); homozygosity for the minor allele (C/C) of the SNP (rs889312) of the gene MAP3K1 was associated with the risk of PMBC (OR = 2.41, 95% CI 1.25-4.63 P-value = .008). Advanced age was protective against PMBC (OR = 0.98, 95% CI 0.95-0.99, P-value = .02). Family history of breast cancer (OR = 2.22, 95% CI 1.14-4.43. P = .02), HRT (OR = 3.35; 95% CI 2.15-5.21, P < .001), and MetS (OR = 14.83, 95% CI 5.63-39.08, P < .001) and interaction between HRT and MetS (OR = 39.38, 95% CI 15.71-98.70, P < .001) were associated with the risk of PMBC. We did not detected significant interactions between SNPs or between the SNPs and the clinico-demographic risk factors. Our study further confirms that MetS increases the risk of PMBC and argues in favor of reducing exposure to HRT. Our findings are another confirmation that low penetrance genes involved in the inflammatory pathway, i.e. MAP3KI gene, may have a plausible causative role in PMBC. Given the fact that genetic constitutionality of individuals cannot be changed, efforts should be focused on life style modification.
PMCID: PMC3858594  PMID: 24340245
Metabolic syndrome; Post-menopausal breast cancer; Chronic inflammation; MAP3K1
11.  Association of germline microRNA SNPs in pre-miRNA flanking region and breast cancer risk and survival: the Carolina Breast Cancer Study 
Cancer causes & control : CCC  2013;24(6):1099-1109.
Common germline variation in the 5′ region proximal to precursor (pre-) miRNA gene sequences is evaluated for association with breast cancer risk and survival among African Americans and Caucasians.
We genotyped 9 single nucleotide polymorphisms (SNPs) within 6 miRNA gene regions previously associated with breast cancer, in 1972 cases and 1776 controls. In a race-stratified analysis using unconditional logistic regression, odds ratios (OR) and 95% confidence intervals (CI) were calculated to evaluate SNP association with breast cancer risk. Additionally, hazard ratios (HR) for breast cancer-specific mortality were estimated.
2 miR-185 SNPs provided suggestive evidence of an inverse association with breast cancer risk (rs2008591, OR = 0.72 (95% CI = 0.53 – 0.98, p-value = 0.04) and rs887205, OR = 0.71 (95% CI = 0.52 – 0.96, p-value = 0.03), respectively) among African Americans. Two SNPs, miR-34b/34c (rs4938723, HR = 0.57 (95% CI = 0.37 – 0.89, p-value = 0.01)) and miR-206 (rs6920648, HR = 0.77 (95% CI = 0.61 – 0.97, p-value = 0.02)), provided evidence of association with breast cancer survival. Further adjustment for stage resulted in more modest associations with survival (HR = 0.65 (95% CI = 0.42 – 1.02, p-value = 0.06 and HR = 0.79 (95% CI = 0.62 – 1.00, p-value = 0.05, respectively).
Our results suggest that germline variation in the 5' region proximal to pre-miRNA gene sequences may be associated with breast cancer risk among African Americans and breast cancer-specific survival generally, however further validation is needed to confirm these findings.
PMCID: PMC3804004  PMID: 23526039
microRNA; breast cancer; germline; single nucleotide polymorphism; risk; survival
12.  Network Signatures of Survival in Glioblastoma Multiforme 
PLoS Computational Biology  2013;9(9):e1003237.
To determine a molecular basis for prognostic differences in glioblastoma multiforme (GBM), we employed a combinatorial network analysis framework to exhaustively search for molecular patterns in protein-protein interaction (PPI) networks. We identified a dysregulated molecular signature distinguishing short-term (survival<225 days) from long-term (survival>635 days) survivors of GBM using whole genome expression data from The Cancer Genome Atlas (TCGA). A 50-gene subnetwork signature achieved 80% prediction accuracy when tested against an independent gene expression dataset. Functional annotations for the subnetwork signature included “protein kinase cascade,” “IκB kinase/NFκB cascade,” and “regulation of programmed cell death” – all of which were not significant in signatures of existing subtypes. Finally, we used label-free proteomics to examine how our subnetwork signature predicted protein level expression differences in an independent GBM cohort of 16 patients. We found that the genes discovered using network biology had a higher probability of dysregulated protein expression than either genes exhibiting individual differential expression or genes derived from known GBM subtypes. In particular, the long-term survivor subtype was characterized by increased protein expression of DNM1 and MAPK1 and decreased expression of HSPA9, PSMD3, and CANX. Overall, we demonstrate that the combinatorial analysis of gene expression data constrained by PPIs outlines an approach for the discovery of robust and translatable molecular signatures in GBM.
Author Summary
Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor in adults, and, while the median survival time for treated patients is approximately one year, subgroups of patients respond differently to the same treatments, with some patients showing little improvement and other patients living far longer than expected. These differences in treatment response indicate that the tumors may show molecular differences that we can harness to tailor cancer therapy. To this end, we sought to identify biomarkers of patient survival in GBM. To improve the applicability of our molecular markers to other patient groups, we constrained our markers using maps of protein-protein interactions, and we also employed a unique computational strategy that incorporates patient-to-patient molecular variability into the results. We identified a set of 50 genes comprising a subnetwork signature that successfully separated GBM patients by their survival times. Our approach to identifying this subnetwork signature also improved our ability to identify its protein products in an independent cohort of patients. In the ongoing search to improve cancer detection and treatment, our work represents a successful strategy for identifying reproducible biomarkers that can more efficiently lead to the discovery of druggable protein targets.
PMCID: PMC3777929  PMID: 24068912
13.  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 
Human genetics  2012;131(9):1507-1517.
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.
PMCID: PMC3604903  PMID: 22688887
Association; Polymorphisms; Glioma; Family history of primary brain tumor; Linkage analysis
14.  Reproductive and Hormonal Risk Factors for Ductal Carcinoma in situ of the Breast 
One-fifth of all newly diagnosed breast cancer cases are ductal carcinoma in situ (DCIS), but little is known about DCIS risk factors. Recent studies suggest that some subtypes of DCIS (high grade, or comedo) share histopathologic and epidemiologic characteristics with invasive disease, while others (medium or low grade, or non-comedo) show different patterns. To investigate whether reproductive and hormonal risk factors differ among comedo and non-comedo types of DCIS and invasive breast cancer, we used a population-based case-control study of 1808 invasive and 446 DCIS breast cancer cases and their age and race frequency-matched controls (1564 invasive and 458 DCIS). Three or more full-term pregnancies showed a strong inverse association with comedo-type DCIS (odds ratio (OR) = 0.53, 95% confidence interval (CI) = 0.30, 0.95) and a weaker inverse association for non-comedo DCIS (OR = 0.73, 95% CI = 0.42, 1.27). Several risk factors (age at first full-term pregnancy, breastfeeding, and age at menopause) demonstrated similar associations for comedo-type DCIS and invasive breast cancer, but different associations for non-comedo DCIS. Ten or more years of oral contraceptive showed a positive association with comedo-type DCIS (OR = 1.31, 05% CI 0.70, 2.47) and invasive breast cancer (OR = 2.33, 95% CI 1.06, 5.09), but an inverse association for noncomedo DCIS (OR = 0.51, 95% CI 0.25-1.04). Our results support the theory that comedo-type DCIS may share hormonal and reproductive risk factors with invasive breast cancer, while the etiology of non-comedo DCIS deserves further investigation.
PMCID: PMC3754830  PMID: 19423528
ductal carcinoma in situ; risk factors; breast cancer; epidemiology; reproductive
16.  Incidence patterns for primary malignant spinal cord gliomas: A Surveillance, Epidemiology, and End Results (SEER) Study 
Journal of neurosurgery. Spine  2011;14(6):742-747.
Primary malignant spinal glioma represents a significant clinical challenge due to the devastating effect on patient clinical outcomes seen in the majority of cases. As they are infrequently encountered in any one center, there has been little population-based data analysis on the incidence patterns of these aggressive tumors. The objective of this study was to use publically available Surveillance, Epidemiology and End Results (SEER) program data to examine overall incidence and incidence patterns over time with regard to patient age at diagnosis, gender, race, primary site of tumor and histological subtype for patients diagnosed with primary malignant spinal cord gliomas between 1973 and 2006.
The study population of interest was limited to primary, malignant, pathologically confirmed spinal cord gliomas using data from the SEER 9 standard registries for patients diagnosed between 1973 and 2006. Variables of interest included age at diagnosis, gender, race, primary site of tumor, and histological subtype of tumor. The SEER*Stat 6.5.2. program was used to calculate frequencies, age-adjusted incidence rates with 95% confidence intervals and annual percentage change (APC) statistics with a 2-sided p-values. In addition, linear correlation coefficients (R2) were calculated for the time association stratified by variables of interest.
The overall age-adjusted incidence rate for primary malignant spinal gliomas was 0.12 per 100,000 and increased significantly over the study time period (APC= 1.74; p-value=0.0004; R2=0.36). Incidence was highest for patients diagnosed at ages 35–49 (0.17 per 100,000), males (0.14 per 100,000), Whites (0.13 per 100,000) and those who had epdenymomas (0.07 per 100,000). Over the study period, the incidence of ependymomas increased significantly (APC = 3.17; p-value<0.0001; R2=0.58) as did the incidence of these tumors in Whites (APC = 2.13; p-value=0.001) and for both males (APC=1.90, p-value<0.0001) and females (APC=1.60, p-value<0.0001). No significant changes in incidence over time by age of diagnosis were found.
This study demonstrates an increasing overall incidence of primary, malignant spinal cord glioma over the past three decades. Notably, for ependymoma the incidence has increased, while the incidence of most other glioma subtypes remained stable. This may be due to improved diagnostic and surgical techniques, changes in histological classification criteria, and changes in neuro-pathology diagnostic criteria. Although rare, an improved understanding of the incidence of these rare tumors will assist investigators and clinicians in planning potential studies and preparing for allocation of resources to care for these challenging patients.
PMCID: PMC3742012  PMID: 21395394
Spinal cord glioma; incidence; patterns over time; population-based; SEER
17.  Identification and molecular characterization of a new ovarian cancer susceptibility locus at 17q21.31 
Permuth-Wey, Jennifer | Lawrenson, Kate | Shen, Howard C. | Velkova, Aneliya | Tyrer, Jonathan P. | Chen, Zhihua | Lin, Hui-Yi | Chen, Y. Ann | Tsai, Ya-Yu | Qu, Xiaotao | Ramus, Susan J. | Karevan, Rod | Lee, Janet | Lee, Nathan | Larson, Melissa C. | Aben, Katja K. | Anton-Culver, Hoda | Antonenkova, Natalia | Antoniou, Antonis | Armasu, Sebastian M. | Bacot, François | Baglietto, Laura | Bandera, Elisa V. | Barnholtz-Sloan, Jill | Beckmann, Matthias W. | Birrer, Michael J. | Bloom, Greg | Bogdanova, Natalia | Brinton, Louise A. | Brooks-Wilson, Angela | Brown, Robert | Butzow, Ralf | Cai, Qiuyin | Campbell, Ian | Chang-Claude, Jenny | Chanock, Stephen | Chenevix-Trench, Georgia | Cheng, Jin Q. | Cicek, Mine S. | Coetzee, Gerhard A. | Cook, Linda S. | Couch, Fergus J. | Cramer, Daniel W. | Cunningham, Julie M. | Dansonka-Mieszkowska, Agnieszka | Despierre, Evelyn | Doherty, Jennifer A | Dörk, Thilo | du Bois, Andreas | Dürst, Matthias | Easton, Douglas F | Eccles, Diana | Edwards, Robert | Ekici, Arif B. | Fasching, Peter A. | Fenstermacher, David A. | Flanagan, James M. | Garcia-Closas, Montserrat | Gentry-Maharaj, Aleksandra | Giles, Graham G. | Glasspool, Rosalind M. | Gonzalez-Bosquet, Jesus | Goodman, Marc T. | Gore, Martin | Górski, Bohdan | Gronwald, Jacek | Hall, Per | Halle, Mari K. | Harter, Philipp | Heitz, Florian | Hillemanns, Peter | Hoatlin, Maureen | Høgdall, Claus K. | Høgdall, Estrid | Hosono, Satoyo | Jakubowska, Anna | Jensen, Allan | Jim, Heather | Kalli, Kimberly R. | Karlan, Beth Y. | Kaye, Stanley B. | Kelemen, Linda E. | Kiemeney, Lambertus A. | Kikkawa, Fumitaka | Konecny, Gottfried E. | Krakstad, Camilla | Kjaer, Susanne Krüger | Kupryjanczyk, Jolanta | Lambrechts, Diether | Lambrechts, Sandrina | Lancaster, Johnathan M. | Le, Nhu D. | Leminen, Arto | Levine, Douglas A. | Liang, Dong | Lim, Boon Kiong | Lin, Jie | Lissowska, Jolanta | Lu, Karen H. | Lubiński, Jan | Lurie, Galina | Massuger, Leon F.A.G. | Matsuo, Keitaro | McGuire, Valerie | McLaughlin, John R | Menon, Usha | Modugno, Francesmary | Moysich, Kirsten B. | Nakanishi, Toru | Narod, Steven A. | Nedergaard, Lotte | Ness, Roberta B. | Nevanlinna, Heli | Nickels, Stefan | Noushmehr, Houtan | Odunsi, Kunle | Olson, Sara H. | Orlow, Irene | Paul, James | Pearce, Celeste L | Pejovic, Tanja | Pelttari, Liisa M. | Pike, Malcolm C. | Poole, Elizabeth M. | Raska, Paola | Renner, Stefan P. | Risch, Harvey A. | Rodriguez-Rodriguez, Lorna | Rossing, Mary Anne | Rudolph, Anja | Runnebaum, Ingo B. | Rzepecka, Iwona K. | Salvesen, Helga B. | Schwaab, Ira | Severi, Gianluca | Shridhar, Vijayalakshmi | Shu, Xiao-Ou | Shvetsov, Yurii B. | Sieh, Weiva | Song, Honglin | Southey, Melissa C. | Spiewankiewicz, Beata | Stram, Daniel | Sutphen, Rebecca | Teo, Soo-Hwang | Terry, Kathryn L. | Tessier, Daniel C. | Thompson, Pamela J. | Tworoger, Shelley S. | van Altena, Anne M. | Vergote, Ignace | Vierkant, Robert A. | Vincent, Daniel | Vitonis, Allison F. | Wang-Gohrke, Shan | Weber, Rachel Palmieri | Wentzensen, Nicolas | Whittemore, Alice S. | Wik, Elisabeth | Wilkens, Lynne R. | Winterhoff, Boris | Woo, Yin Ling | Wu, Anna H. | Xiang, Yong-Bing | Yang, Hannah P. | Zheng, Wei | Ziogas, Argyrios | Zulkifli, Famida | Phelan, Catherine M. | Iversen, Edwin | Schildkraut, Joellen M. | Berchuck, Andrew | Fridley, Brooke L. | Goode, Ellen L. | Pharoah, Paul D. P. | Monteiro, Alvaro N.A. | Sellers, Thomas A. | Gayther, Simon A.
Nature communications  2013;4:1627.
Epithelial ovarian cancer (EOC) has a heritable component that remains to be fully characterized. Most identified common susceptibility variants lie in non-protein-coding sequences. We hypothesized that variants in the 3′ untranslated region at putative microRNA (miRNA) binding sites represent functional targets that influence EOC susceptibility. Here, we evaluate the association between 767 miRNA binding site single nucleotide polymorphisms (miRSNPs) and EOC risk in 18,174 EOC cases and 26,134 controls from 43 studies genotyped through the Collaborative Oncological Gene-environment Study. We identify several miRSNPs associated with invasive serous EOC risk (OR=1.12, P=10−8) mapping to an inversion polymorphism at 17q21.31. Additional genotyping of non-miRSNPs at 17q21.31 reveals stronger signals outside the inversion (P=10−10). Variation at 17q21.31 associates with neurological diseases, and our collaboration is the first to report an association with EOC susceptibility. An integrated molecular analysis in this region provides evidence for ARHGAP27 and PLEKHM1 as candidate EOC susceptibility genes.
PMCID: PMC3709460  PMID: 23535648
18.  A nomogram for individualized estimation of survival among patients with brain metastasis 
Neuro-Oncology  2012;14(7):910-918.
Purpose: An estimated 24%–45% of patients with cancer develop brain metastases. Individualized estimation of survival for patients with brain metastasis could be useful for counseling patients on clinical outcomes and prognosis. Methods: De-identified data for 2367 patients with brain metastasis from 7 Radiation Therapy Oncology Group randomized trials were used to develop and internally validate a prognostic nomogram for estimation of survival among patients with brain metastasis. The prognostic accuracy for survival from 3 statistical approaches (Cox proportional hazards regression, recursive partitioning analysis [RPA], and random survival forests) was calculated using the concordance index. A nomogram for 12-month, 6-month, and median survival was generated using the most parsimonious model. Results: The majority of patients had lung cancer, controlled primary disease, no surgery, Karnofsky performance score (KPS) ≥ 70, and multiple brain metastases and were in RPA class II or had a Diagnosis-Specific Graded Prognostic Assessment (DS-GPA) score of 1.25–2.5. The overall median survival was 136 days (95% confidence interval, 126–144 days). We built the nomogram using the model that included primary site and histology, status of primary disease, metastatic spread, age, KPS, and number of brain lesions. The potential use of individualized survival estimation is demonstrated by showing the heterogeneous distribution of the individual 12-month survival in each RPA class or DS-GPA score group. Conclusion: Our nomogram provides individualized estimates of survival, compared with current RPA and DS-GPA group estimates. This tool could be useful for counseling patients with respect to clinical outcomes and prognosis.
PMCID: PMC3379797  PMID: 22544733
brain metastases; nomogram; prediction; prognosis; survival
19.  Prevalence and Predictors of Interval Colorectal Cancers in Medicare Beneficiaries 
Cancer  2011;118(12):3044-3052.
Following a colonoscopy that is negative for cancer, a subset of patients may be diagnosed with colorectal cancer, also termed interval cancer. The frequency and predictors have not been well studied in a population-based U.S. cohort.
Using the linked SEER-Medicare database, we identified 57,839 patients aged ≥ 69 with colorectal cancer diagnosed between 1994 and 2005 and who underwent colonoscopy within 6 months of cancer diagnosis. Colonoscopy performed between 36 to 6 months prior to cancer diagnosis was a proxy for interval cancer.
Using the case definition, 7.2% of patients developed interval cancers. Factors associated with interval cancers included proximal tumor location (distal colon multivariable OR 0.42, 95% CI 0.390–0.46, rectum OR 0.47, 95% CI 0.42–0.53), increased comorbidity (OR 1.89 95% CI 1.68 2.14 for 3 or more comorbidities), a previous diagnosis of diverticulosis (OR 6.00 95% CI 5.57–6.46), and prior polypectomy (OR 1.74, 95% CI 1.62–1.87). Risk factors at the endoscopist level included a lower polypectomy rate (OR 0.70, 95% CI 0.63–0.78 for the highest quartile), higher colonoscopy volume (OR 1.27, 95% CI 1.13–1.43) and specialty other than gastroenterology (colorectal surgery OR 1.45, 95% CI 1.16–1.83; general surgery OR 1.42, 95% CI 1.24–1.62; internal medicine OR 1.38, 95% CI 1.17–1.63, family practice OR 1.16, 95% CI 1.00–1.35).
A significant proportion of patients develop interval colorectal cancer, particularly in the proximal colon. Contributing factors likely include both procedural and biologic factors, and emphasize the importance of meticulous examination of the mucosa.
PMCID: PMC3258472  PMID: 21989586
20.  Aberrant Vimentin Methylation Is Characteristic of Upper Gastrointestinal Pathologies 
We have previously established aberrant DNA methylation of Vimentin exon-1 (VIM methylation) as a common epigenetic event in colon cancer and as a biomarker for detecting colon neoplasia. We now examine VIM methylation in neoplasia of the upper gastrointestinal tract.
Using a quantitative real-time Methylation-Specific PCR assay we tested for VIM methylation in archival specimens of esophageal and gastric neoplasia.
We find that acquisition of aberrant VIM methylation is highly common in these neoplasms, but largely absent in controls. The highest frequency of VIM methylation was detected in lesions of the distal esophagus, including 91% of Barrett’s esophagus (BE, n=11), 100% of high grade dysplasia (HGD, n=5), and 81% of esophageal adenocarcinoma (EAC, n=26), but absent in controls (n=9). VIM methylation similarly was detected in 87% of signet ring (n=15) and 53% of intestinal type gastric cancers (n=17). Moreover, in tests of cytology brushings VIM methylation proved detectable in 100% of BE cases (n=7), 100% of HGD cases (n=4), and 83% of EAC cases (n=18), but was absent in all controls (n=5).
These findings establish aberrant VIM methylation as a highly common epigenetic alteration in neoplasia of the upper gastrointestinal tract, and demonstrate that Barrett’s esophagus, even without dysplasia, already contains epigenetic alterations characteristic of adenocarcinoma.
These findings suggest VIM methylation as a biomarker of upper gastrointestinal neoplasia with potential for development as molecular cytology in esophageal screening.
PMCID: PMC3454489  PMID: 22315367
Barrett’s Esophagus; Esophageal Cancer; Gastric Cancer; Vimentin; Methylation
21.  Genetic Ancestry, Skin Reflectance and Pigmentation Genotypes in Association with Serum Vitamin D Metabolite Balance 
Lower serum vitamin D (25(OH)D) among individuals with African ancestry is attributed primarily to skin pigmentation. However, the influence of genetic polymorphisms controlling for skin melanin content has not been investigated. Therefore, we investigated differences in non-summer serum vitamin D metabolites according to self-reported race, genetic ancestry, skin reflectance and key pigmentation genes (SLC45A2 and SLC24A5).
Materials and Methods
Healthy individuals reporting at least half African American or half European American heritage were frequency matched to one another on age (+/− 2 years) and sex. 176 autosomal ancestry informative markers were used to estimate genetic ancestry. Melanin index was measured by reflectance spectrometry. Serum vitamin D metabolites (25(OH)D3, 25(OH)D2 and 24,25(OH)2D3) were determined by high performance liquid chromatography (HPLC) tandem mass spectrometry. Percent 24,25(OH)2D3 was calculated as a percent of the parent metabolite (25(OH)D3). Stepwise and backward selection regression models were used to identify leading covariates.
Fifty African Americans and 50 European Americans participated in the study. Compared with SLC24A5 111Thr homozygotes, individuals with the SLC24A5 111Thr/Ala and 111Ala/Ala genotypes had respectively lower levels of 25(OH)D3 (23.0 and 23.8 nmol/L lower, p-dominant=0.007), and percent 24,25(OH)2D3 (4.1 and 5.2 percent lower, p-dominant=0.003), controlling for tanning bed use, vitamin D/fish oil supplement intake, race/ethnicity, and genetic ancestry. Results were similar with melanin index adjustment, and were not confounded by glucocorticoid, oral contraceptive, or statin use.
The SLC24A5 111Ala allele was associated with lower serum vitamin 25(OH)D3 and lower percent 24,25(OH)2D3, independently from melanin index and West African genetic ancestry.
PMCID: PMC3606023  PMID: 23525585
African Continental Ancestry Group; European Continental Ancestry Group; SLC24A5; 25-hydroxyvitamin D; 24,25-Dihydroxyvitamin D 3
22.  Variation In Age At Cancer Diagnosis In Familial Versus Non-Familial Barrett’s Esophagus 
Genetic influences may be discerned in families that have multiple affected members and may manifest as an earlier age of cancer diagnosis. In this study we determine whether cancers develop at an earlier age in multiplex Familial Barrett’s Esophagus (FBE) kindreds, defined by 3 or more members affected by Barrett’s esophagus (BE) or esophageal adenocarcinoma (EAC).
Information on BE/EAC risk factors and family history was collected from probands at eight tertiary care academic hospitals. Age of cancer diagnosis and other risk factors were compared between non-familial (no affected relatives), duplex (two affected relatives), and multiplex (three or more affected relatives) FBE kindreds.
The study included 830 non-familial, 274 duplex and 41 multiplex FBE kindreds with 274, 133 and 43 EAC and 566, 288 and 103 BE cases, respectively. Multivariable mixed models adjusting for familial correlations showed that multiplex kindreds were associated with a younger age of cancer diagnosis (p = 0.0186). Median age of cancer diagnosis was significantly younger in multiplex compared to duplex and non-familial kindreds (57 vs. 62 vs. 63 yrs, respectively, p = 0.0448). Mean body mass index (BMI) was significantly lower in multiplex kindreds (p = 0.0033) as was smoking (p < 0.0001), and reported regurgitation (p = 0.0014).
Members of multiplex FBE kindreds develop EAC at an earlier age compared to non-familial EAC cases. Multiplex kindreds do not have a higher proportion of common risk factors for EAC, suggesting that this aggregation might be related to a genetic factor.
These findings indicate that efforts to identify susceptibility genes for BE and EAC will need to focus on multiplex kindreds.
PMCID: PMC3275661  PMID: 22178570
Esophageal adenocarcinoma; Barrett’s esophagus; genetics; family history
23.  The MicroRNAs, MiR-31 and MiR-375, as Candidate Markers in Barrett's Esophageal Carcinogenesis 
Genes, chromosomes & cancer  2012;51(5):473-479.
There is a critical need to identify molecular markers that can reliably aid in stratifying esophageal adenocarcinoma (EAC) risk in patients with Barrett's esophagus. MicroRNAs (miRNA/miR) are one such class of biomolecules. In the present cross-sectional study, we characterized miRNA alterations in progressive stages of neoplastic development, i.e., metaplasia–dysplasia–adenocarcinoma, with an aim to identify candidate miRNAs potentially associated with progression. Using next generation sequencing (NGS) as an agnostic discovery platform, followed by quantitative real-time PCR (qPCR) validation in a total of 20 EACs, we identified 26 miRNAs that are highly and frequently deregulated in EACs (≥4-fold in >50% of cases) when compared to paired normal esophageal squamous (nSQ) tissue. We then assessed the 26 EAC-derived miRNAs in laser microdissected biopsy pairs of Barrett's metaplasia (BM)/nSQ (n = 15), and high-grade dysplasia (HGD)/nSQ (n = 14) by qPCR, to map the timing of deregulation during progression from BM to HGD and to EAC. We found that 23 of the 26 candidate miRNAs were deregulated at the earliest step, BM, and therefore noninformative as molecular markers of progression. Two miRNAs, miR-31 and –31*, however, showed frequent downregulation only in HGD and EAC cases suggesting association with transition from BM to HGD. A third miRNA, miR-375, showed marked downregulation exclusively in EACs and in none of the BM or HGD lesions, suggesting its association with progression to invasive carcinoma. Taken together, we propose miR-31 and –375 as novel candidate microRNAs specifically associated with early- and late-stage malignant progression, respectively, in Barrett's esophagus.
PMCID: PMC3547654  PMID: 22302717
24.  Genome-wide high-density SNP linkage search for glioma susceptibility loci: results from the Gliogene Consortium 
Cancer research  2011;71(24):7568-7575.
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.
PMCID: PMC3242820  PMID: 22037877
Glioma; family studies; linkage; haplotype pattern; NPL
25.  Identifying stage-specific protein subnetworks for colorectal cancer 
BMC Proceedings  2012;6(Suppl 7):S1.
In recent years, many algorithms have been developed for network-based analysis of differential gene expression in complex diseases. These algorithms use protein-protein interaction (PPI) networks as an integrative framework and identify subnetworks that are coordinately dysregulated in the phenotype of interest.
While such dysregulated subnetworks have demonstrated significant improvement over individual gene markers for classifying phenotype, the current state-of-the-art in dysregulated subnetwork discovery is almost exclusively limited to binary phenotype classes. However, many clinical applications require identification of molecular markers for multiple classes.
We consider the problem of discovering groups of genes whose expression signatures can discriminate multiple phenotype classes. We consider two alternate formulations of this problem (i) an all-vs-all approach that aims to discover subnetworks distinguishing all classes, (ii) a one-vs-all approach that aims to discover subnetworks distinguishing each class from the rest of the classes. For the one-vs-all formulation, we develop a set-cover based algorithm, which aims to identify groups of genes such that at least one gene in the group exhibits differential expression in the target class.
We test the proposed algorithms in the context of predicting stages of colorectal cancer. Our results show that the set-cover based algorithm identifying "stage-specific" subnetworks outperforms the all-vs-all approaches in classification. We also investigate the merits of utilizing PPI networks in the search for multiple markers, and show that, with correct parameter settings, network-guided search improves performance. Furthermore, we show that assessing statistical significance when selecting features greatly improves classification performance.
PMCID: PMC3504924  PMID: 23173715

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