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
genome-wide association; family studies; study designs; genetic factors; environmental factors
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.
The revolution in sequencing techniques in the past decade has provided an extensive picture of the molecular mechanisms behind complex diseases such as cancer. The Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Project (CGP) have provided an unprecedented opportunity to examine copy number, gene expression, and mutational information for over 1000 cell lines of multiple tumor types alongside IC50 values for over 150 different drugs and drug related compounds. We present a novel pipeline called DIRPP, Drug Intervention Response Predictions with PARADIGM7, which predicts a cell line’s response to a drug intervention from molecular data. PARADIGM (Pathway Recognition Algorithm using Data Integration on Genomic Models) is a probabilistic graphical model used to infer patient specific genetic activity by integrating copy number and gene expression data into a factor graph model of a cellular network. We evaluated the performance of DIRPP on endometrial, ovarian, and breast cancer related cell lines from the CCLE and CGP for nine drugs. The pipeline is sensitive enough to predict the response of a cell line with accuracy and precision across datasets as high as 80 and 88% respectively. We then classify drugs by the specific pathway mechanisms governing drug response. This classification allows us to compare drugs by cellular response mechanisms rather than simply by their specific gene targets. This pipeline represents a novel approach for predicting clinical drug response and generating novel candidates for drug repurposing and repositioning.
The Brain Tumor Epidemiology Consortium (BTEC) is an open scientific forum, which fosters the development of multi-center, international and inter-disciplinary collaborations. BTEC aims to develop a better understanding of the etiology, outcomes, and prevention of brain tumors (http://epi.grants.cancer.gov/btec/). The 15th annual Brain Tumor Epidemiology Consortium Meeting, hosted by the Austrian Societies of Neuropathology and Neuro-oncology, was held on September 9 – 11, 2014 in Vienna, Austria. The meeting focused on the central role of brain tumor epidemiology within multidisciplinary neuro-oncology. Knowledge of disease incidence, outcomes, as well as risk factors is fundamental to all fields involved in research and treatment of patients with brain tumors; thus, epidemiology constitutes an important link between disciplines, indeed the very hub. This was reflected by the scientific program, which included various sessions linking brain tumor epidemiology with clinical neuro-oncology, tissue-based research, and cancer registration. Renowned experts from Europe and the United States contributed their personal perspectives stimulating further group discussions. Several concrete action plans evolved for the group to move forward until next year’s meeting, which will be held at the Mayo Clinic at Rochester, MN, USA.
brain tumor; epidemiology; clinical research; tissue-based research; risk factor research
Cancer is responsible for approximately 7.6 million deaths per year worldwide. A 2012 survey in the United Kingdom found dramatic improvement in survival rates for childhood cancer because of increased participation in clinical trials. Unfortunately, overall patient participation in cancer clinical studies is low. A key logistical barrier to patient and physician participation is the time required for identification of appropriate clinical trials for individual patients. We introduce the Trial Prospector tool that supports end-to-end management of cancer clinical trial recruitment workflow with (a) structured entry of trial eligibility criteria, (b) automated extraction of patient data from multiple sources, (c) a scalable matching algorithm, and (d) interactive user interface (UI) for physicians with both matching results and a detailed explanation of causes for ineligibility of available trials. We report the results from deployment of Trial Prospector at the National Cancer Institute (NCI)-designated Case Comprehensive Cancer Center (Case CCC) with 1,367 clinical trial eligibility evaluations performed with 100% accuracy.
clinical trial; gastrointestinal cancer; clinical oncology; patient recruitment; clinical decision support system
Gene markers or biomarkers can be used for diagnostic or prognostic purposes for all different types of complex disease, including brain tumors. Prognostic markers can be useful to not only explain differences in overall survival but also for differences in response to treatment and for development of targeted therapies. Multiple genes with specific types of alterations have now been identified that are associated with improved response to chemotherapy and radiotherapy, such as o6-methylguanine methyltranferase (MGMT) or loss of chromosomes 1p and/or 19q. Other alterations have been identified that are associated with improved overall survival, such as mutations in isocitrate dehydrogenase 1 (IDH1) and/or isocitrate dehydrogenase 2 (IDH2) or having the glioma CpG island DNA methylator phenotype (G-CIMP). There are many biomarkers that may have relevance in brain tumor associated epilepsy that does not respond to treatment. Given the rapidly changing landscape of high throughput “omics” technologies, there is significant potential for gaining further knowledge via integration of multiple different types of high genome wide data. This knowledge can be translated into improved therapies and clinical outcomes for brain tumor patients.
Biomarker; Epilepsy; Brain tumor; MGMT; IDH1; IDH2; LEAT; G-CIMP
A challenge in precision medicine is the transformation of genomic data into knowledge that can be used to stratify patients into treatment groups based on predicted clinical response. Although clinical trials remain the only way to truly measure drug toxicities and effectiveness, as a scientific community we lack the resources to clinically assess all drugs presently under development. Therefore, an effective preclinical model system that enables prediction of anticancer drug response could significantly speed the broader adoption of personalized medicine.
Three large-scale pharmacogenomic studies have screened anticancer compounds in greater than 1000 distinct human cancer cell lines. We combined these datasets to generate and validate multi-omic predictors of drug response. We compared drug response signatures built using a penalized linear regression model and two non-linear machine learning techniques, random forest and support vector machine. The precision and robustness of each drug response signature was assessed using cross-validation across three independent datasets. Fifteen drugs were common among the datasets. We validated prediction signatures for eleven out of fifteen tested drugs (17-AAG, AZD0530, AZD6244, Erlotinib, Lapatinib, Nultin-3, Paclitaxel, PD0325901, PD0332991, PF02341066, and PLX4720).
Multi-omic predictors of drug response can be generated and validated for many drugs. Specifically, the random forest algorithm generated more precise and robust prediction signatures when compared to support vector machines and the more commonly used elastic net regression. The resulting drug response signatures can be used to stratify patients into treatment groups based on their individual tumor biology, with two major benefits: speeding the process of bringing preclinical drugs to market, and the repurposing and repositioning of existing anticancer therapies.
We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.
Ovarian cancer (OVCA) is the leading cause of death from gynecological cancer, with poorer survival for African American (AA) women compared to whites. However, little is known about risk factors for OVCA in AA. To study the epidemiology of OVCA in this population, we started a collaborative effort in 10 sites in the US. Here we describe the study and highlight the challenges of conducting a study of a lethal disease in a minority population.
The African American Cancer Epidemiology Study (AACES) is an ongoing, population-based case–control study of OVCA in AA in 10 geographic locations, aiming to recruit 850 women with invasive epithelial OVCA and 850 controls age- and geographically-matched to cases. Rapid case ascertainment and random-digit-dialing systems are in place to ascertain cases and controls, respectively. A telephone survey focuses on risk factors as well as factors of particular relevance for AAs. Food-frequency questionnaires, follow-up surveys, biospecimens and medical records are also obtained.
Current accrual of 403 AA OVCA cases and 639 controls exceeds that of any existing study to date. We observed a high proportion (15%) of deceased non-responders among the cases that in part is explained by advanced stage at diagnosis. A logistic regression model did not support that socio-economic status was a factor in advanced stage at diagnosis. Most risk factor associations were in the expected direction and magnitude. High BMI was associated with ovarian cancer risk, with multivariable adjusted ORs and 95% CIs of 1.50 (0.99-2.27) for obese and 1.27 (0.85- 1.91) for morbidly obese women compared to normal/underweight women.
AACES targets a rare tumor in AAs and addresses issues most relevant to this population. The importance of the study is accentuated by the high proportion of OVCA cases ascertained as deceased. Our analyses indicated that obesity, highly prevalent in this population (>60% of the cases), was associated with increased OVCA risk. While these findings need to be replicated, they suggest the potential for an effective intervention on the risk in AAs. Upon completion of enrollment, AACES will be the largest epidemiologic study of OVCA in AA women.
Epidemiology; Ovarian cancer; African American; Case–control study
There are currently no molecular targeted approaches to treat small-cell lung cancer (SCLC) similar to those used successfully against non-small-cell lung cancer. This failure is attributable to our inability to identify clinically-relevant subtypes of this disease. Thus, a more systematic approach to drug discovery for SCLC is needed. In this regard, two comprehensive studies recently published in Nature, the Cancer Cell Line Encyclopedia and the Cancer Genome Project, provide a wealth of data regarding the drug sensitivity and genomic profiles of many different types of cancer cells. In the present study we have mined these two studies for new therapeutic agents for SCLC and identified heat shock proteins, cyclin-dependent kinases and polo-like kinases (PLK) as attractive molecular targets with little current clinical trial activity in SCLC. Remarkably, our analyses demonstrated that most SCLC cell lines clustered into a single, predominant subgroup by either gene expression or CNV analyses, leading us to take a pharmacogenomic approach to identify subgroups of drug-sensitive SCLC cells. Using PLK inhibitors as an example, we identified and validated a gene signature for drug sensitivity in SCLC cell lines. This gene signature could distinguish subpopulations among human SCLC tumors, suggesting its potential clinical utility. Finally, circos plots were constructed to yield a comprehensive view of how transcriptional, copy number and mutational elements affect PLK sensitivity in SCLC cell lines. Taken together, this study outlines an approach to predict drug sensitivity in SCLC to novel targeted therapeutics.
Background & Aims
15-hydroxprostaglandin dehydrogenase (15-PGDH) mediates a colon neoplasia suppressor pathway, acting through metabolic antagonism of cyclooxygenase (COX)-mediated colon carcinogenesis. To determine whether the colon tumor prevention activity of 15-PGDH acts as a constant or variable effect among individuals, we determined whether 15-PGDH levels remains stable over subsite and time in the human colon, determined the extent of differences in 15-PGDH levels between different individuals, and determined whether or not 15-PGDH modulation mediates any part of the anti-colon tumor effect of aspirin.
Using real-time PCR, we measured 15-PGDH mRNA, determining the correlation of 15-PGDH level in replicate colon biopsies, in biopsies from throughout the length of the colon, in repeat biopsies taken 4 months apart, and in paired biopsies of individuals taken before and after aspirin treatment, and by western for 15-PGDH protein in mice.
Colonic 15-PGDH levels varied 4.4-fold across the human population. Within individuals, 15-PGDH levels proved highly reproducible (r=0.81 in duplicate biopsies) and stable along the length of the colon, with average 15-PGDH levels deviating by only 17% from rectum to cecum. An individual’s 15-PGDH levels are also highly stable over time, with a median coefficient of variation over a 4-month interval of only 12%. Last, colonic 15-PGDH levels proved resistant to alteration by aspirin, with only a 10% difference in 15-PGDH levels measured before and after aspirin treatment.
15-PGDH levels vary across the population in a stable and reproducible manner, and are resistant to alteration by aspirin. 15-PGDH represents an independent target for modulation by candidate colon tumor chemopreventive agents.
Colon Cancer; 15-PGDH; NSAIDs; Biomarker
Human immunodeficiency virus (HIV) infection contributes to accelerated rates of progression of liver fibrosis during hepatitis C virus (HCV) infection, and HCV liver disease contributes to mortality during HIV infection. Although mechanisms underlying these interactions are not well known, soluble and cellular markers of immune activation associate with disease progression during both infections.
We identified proteins varying in expression across the plasma proteomes of subjects with untreated HIV infection, untreated HCV infection with low AST/platelet ratio-index (APRI), untreated HCV infection with high APRI, HIV-HCV co-infection, and controls. We examined correlations between dysregulated proteins and markers of immune activation to uncover biomarkers specific to disease states.
We observed the anticipated higher frequencies of HLADR+CD38+CD4 and CD8 T-cells, higher serum sCD14 levels, and higher serum IL-6 levels for HCV and HIV infected groups compared to controls. Plasma proteome analysis identified 2,297 peptides mapping to 227 proteins, and quantitative analysis of peptide intensity identified significant changes in 85 proteins across the five groups. Abundance for seven of these proteins was validated by ELISA. Forty-three of these proteins correlated with markers of immune activation, including at least two proteins that may directly drive T-cell activation. As a functional validation, we tested the enzymatic pathway product (lysophosphatidic acid, LPA) of one such protein, ENPP2, for ability to activate T-cells in vitro. LPA activated T-cells to express CD38 and HLA-DR.
These data indicate elevated levels of ENPP2 and LPA during advanced HCV disease may play a role in exacerbating immune activation during HCV-HIV co-infection.
Heavy alcohol consumption increases risk of developing squamous cell carcinoma of the head and neck (SCCHN). Alcohol metabolism to cytotoxic and mutagenic intermediates acetaldehyde and reactive oxygen species is critical for alcohol-drinking-associated carcinogenesis. We hypothesized that polymorphisms in alcohol metabolism-related and antioxidant genes influence SCCHN survival.
Interview and genotyping data (64 polymorphisms in 12 genes) were obtained from 1227 white and African-American cases from the Carolina Head and Neck Cancer Epidemiology study, a population-based case–control study of SCCHN conducted in North Carolina from 2002 to 2006. Vital status, date and cause of death through 2009 were obtained from the National Death Index. Kaplan–Meier log-rank tests and adjusted hazard ratios were calculated to identify alleles associated with survival.
Most tested SNPs were not associated with survival, with the exception of the minor alleles of rs3813865 and rs8192772 in CYP2E1. These were associated with poorer cancer-specific survival (HRrs3813865, 95%CI = 2.00, 1.33–3.01; HRrs8192772, 95%CI = 1.62, 1.17–2.23). Hazard ratios for 8 additional SNPs in CYP2E1, GPx2, SOD1, and SOD2, though not statistically significant, were suggestive of differences in allele hazards for all-cause and/or cancer death. No consistent associations with survival were found for SNPs in ADH1B, ADH1C, ADH4, ADH7, ALDH2, GPx2, GPx4, and CAT.
We identified some polymorphisms in alcohol and oxidative stress metabolism genes that influence survival in subjects with SCCHN. Previously unreported associations of SNPs in CYP2E1 warrant further investigation.
Head and neck neoplasms/epidemiology; Genes; Survival; Alcohol drinking/metabolism; Oxidative stress
Cigarette smoking is associated with increased head and neck cancer (HNC) risk. Tobacco-related carcinogens are known to cause bulky DNA adducts. Nucleotide excision repair (NER) genes encode enzymes that remove adducts and may be independently associated with HNC, as well as modifiers of the association between smoking and HNC.
Using population-based case-control data from the Carolina Head and Neck Cancer Epidemiology Study (1,227 cases, 1,325 controls), race-stratified (white, African American) conventional and hierarchical logistic regression models were utilized to estimate odds ratios (OR) with 95% intervals (I) for the independent and joint effects of cigarette smoking and 84 single nucleotide polymorphisms (SNPs) from 15 NER genes on HNC risk.
The odds of HNC were elevated among ever cigarette smokers, and increased with smoking duration and frequency. Among whites, rs4150403 on ERCC3 was associated with increased HNC odds (AA+AG vs. GG, OR=1.28, 95% I=1.01,1.61). Among African Americans, rs4253132 on ERCC6 was associated with decreased HNC odds (CC+CT vs. TT, OR=0.62, 95% I=0.45,0.86). Interactions between ever cigarette smoking and three SNPs (rs4253132 on ERCC6, rs2291120 on DDB2, and rs744154 on ERCC4) suggested possible departures from additivity among whites.
We did not find associations between some previously studied NER variants and HNC. We did identify new associations between two SNPs and HNC and three suggestive cigarette-SNP interactions to consider in future studies.
We conducted one of the most comprehensive evaluations of NER variants, identifying a few SNPs from biologically plausible candidate genes associated with HNC and possibly interacting with cigarette smoking.
Head and neck/oral cancers; DNA damage and repair mechanisms; DNA repair polymorphisms and risk; tobacco
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.
Head and neck cancer DNA repair; Nucleotide excision repair; Chemotherapy; Radiation; Survival
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
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.
Central nervous system cancer; Subsequent cancer; Radiotherapy; Surveillance, Epidemiology and End Results (SEER) Program
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.
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.
TP53; RB1; LGI1; glioblastoma; brain tumors; mutation analysis
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.
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.
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.
tocopherol; oxidative stress; single nucleotide polymorphism
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.
Glioma; model-based linkage; segregation; age of onset; prevalence constraint