Epigenetic alterations are a common event in lung cancer and their identification can serve to inform on the carcinogenic process and provide clinically relevant biomarkers. Using paired tumor and non-tumor lung tissues from 146 individuals from three independent populations we sought to identify common changes in DNA methylation associated with the development of non-small cell lung cancer. Pathologically normal lung tissue taken at the time of cancer resection was matched to tumorous lung tissue and together were probed for methylation using Illumina GoldenGate arrays in the discovery set (n = 47 pairs) followed by bisulfite pyrosequencing for validation sets (n = 99 pairs). For each matched pair the change in methylation at each CpG was calculated (the odds ratio), and these ratios were averaged across individuals and ranked by magnitude to identify the CpGs with the greatest change in methylation associated with tumor development. We identified the top gene-loci representing an increase in methylation (HOXA9, 10.3-fold and SOX1, 5.9-fold) and decrease in methylation (DDR1, 8.1-fold). In replication testing sets, methylation was higher in tumors for HOXA9 (p < 2.2 × 10−16) and SOX1 (p < 2.2 × 10−16) and lower for DDR1 (p < 2.2 × 10−16). The magnitude and strength of these changes were consistent across squamous cell and adenocarcinoma tumors. Our data indicate that the identified genes consistently have altered methylation in lung tumors. Our identified genes should be included in translational studies that aim to develop screening for early disease detection.
DNA Methylation; goldengate; lung cancer; molecular epidemiology; pyrosequencing
Although much is known about molecular and chromosomal characteristics that distinguish glioma histological subtypes, DNA methylation patterns of gliomas and their association with other tumor features such as mutation of isocitrate dehydrogenase (IDH) genes have only recently begun to be investigated.
DNA methylation of glioblastomas, astrocytomas, oligodendrogliomas, oligoastrocytomas, ependymomas, and pilocytic astrocytomas (n = 131) from the Brain Tumor Research Center at the University of California San Francisco, as well as nontumor brain tissues (n = 7), was assessed with the Illumina GoldenGate methylation array. Methylation data were subjected to recursively partitioned mixture modeling (RPMM) to derive methylation classes. Differential DNA methylation between tumor and nontumor was also assessed. The association between methylation class and IDH mutation (IDH1 and IDH2) was tested using univariate and multivariable analysis for tumors (n = 95) with available substrate for sequencing. Survival of glioma patients carrying mutant IDH (n = 57) was compared with patients carrying wild-type IDH (n = 38) using a multivariable Cox proportional hazards model and Kaplan–Meier analysis. All statistical tests were two-sided.
We observed a statistically significant association between RPMM methylation class and glioma histological subtype (P < 2.2 × 10−16). Compared with nontumor brain tissues, across glioma tumor histological subtypes, the differential methylation ratios of CpG loci were statistically significantly different (permutation P < .0001). Methylation class was strongly associated with IDH mutation in gliomas (P = 3.0 × 10−16). Compared with glioma patients whose tumors harbored wild-type IDH, patients whose tumors harbored mutant IDH showed statistically significantly improved survival (hazard ratio of death = 0.27, 95% confidence interval = 0.10 to 0.72).
The homogeneity of methylation classes for gliomas with IDH mutation, despite their histological diversity, suggests that IDH mutation is associated with a distinct DNA methylation phenotype and an altered metabolic profile in glioma.
Acute lymphoblastic leukemia (ALL) likely has a multistep etiology, with initial genetic aberrations occurring early in life. An abnormal immune response to common infections has emerged as a plausible candidate for triggering the proliferation of pre-leukemic clones and the fixation of secondary genetic mutations and epigenetic alterations. We investigated whether evidence of infection with a specific common myelotropic childhood virus, parvovirus B19 (PVB19), relates to patterns of gene promoter DNA methylation in ALL patients. We serologically tested bone marrow samples at diagnosis of B-cell ALL for PVB19 infection and DNA methylation using a high-throughput bead array and found that 4.2% and 36.7% of samples were seroreactive to PVB19 IgM and IgG, respectively. Leukemia samples were grouped by DNA methylation pattern. Controlling for age and immunophenotype, unsupervised modeling confirmed that the DNA methylation pattern was associated with history of PVB19 (assessed by IgG, p = 0.02), but not recent infection (assessed by IgM). Replication assays on single genes were consistent with the association. The data indicate that a common viral illness may drive specific DNA methylation patterns in susceptible B-precursor cells, contributing to the leukemogenic potential of such cells. Infections may impact childhood leukemia by altering DNA methylation patterns and specific key genes in susceptible cells; these changes may be retained even after the clearance of infection.
childhood leukemia; DNA methylation; parvovirus B19; serology
Approximately 500,000 individuals diagnosed with bladder cancer in the U.S. require routine cystoscopic follow-up to monitor for disease recurrences or progression, resulting in over $2 billion in annual expenditures. Identification of new diagnostic and monitoring strategies are clearly needed, and markers related to DNA methylation alterations hold great promise due to their stability, objective measurement, and known associations with the disease and with its clinical features. To identify novel epigenetic markers of aggressive bladder cancer, we utilized a high-throughput DNA methylation bead-array in two distinct population-based series of incident bladder cancer (n = 73 and n = 264, respectively). We then validated the association between methylation of these candidate loci with tumor grade in a third population (n = 245) through bisulfite pyrosequencing of candidate loci. Array based analyses identified 5 loci for further confirmation with bisulfite pyrosequencing. We identified and confirmed that increased promoter methylation of HOXB2 is significantly and independently associated with invasive bladder cancer and methylation of HOXB2, KRT13 and FRZB together significantly predict high-grade non-invasive disease. Methylation of these genes may be useful as clinical markers of the disease and may point to genes and pathways worthy of additional examination as novel targets for therapeutic treatment.
Motivation: Integration of various genome-scale measures of molecular alterations is of great interest to researchers aiming to better define disease processes or identify novel targets with clinical utility. Particularly important in cancer are measures of gene copy number DNA methylation. However, copy number variation may bias the measurement of DNA methylation. To investigate possible bias, we analyzed integrated data obtained from 19 head and neck squamous cell carcinoma (HNSCC) tumors and 23 mesothelioma tumors.
Results: Statistical analysis of observational data produced results consistent with those anticipated from theoretical mathematical properties. Average beta value reported by Illumina GoldenGate (a bead-array platform) was significantly smaller than a similar measure constructed from the ratio of average dye intensities. Among CpGs that had only small variations in measured methylation across tumors (filtering out clearly biological methylation signatures), there were no systematic copy number effects on methylation for three and more than four copies; however, one copy led to small systematic negative effects, and no copies led to substantial significant negative effects.
Conclusions: Since mathematical considerations suggest little bias in methylation assayed using bead-arrays, the consistency of observational data with anticipated properties suggests little bias. However, further analysis of systematic copy number effects across CpGs suggest that though there may be little bias when there are copy number gains, small biases may result when one allele is lost, and substantial biases when both alleles are lost. These results suggest that further integration of these measures can be useful for characterizing the biological relationships between these somatic events.
Supplementary information: Supplementary data are available at Bioinformatics online.
Pathologic differentiation of tissue of origin in tumors found in the lung can be challenging, with differentiation of mesothelioma and lung adenocarcinoma emblematic of this problem. Indeed, proper classification is essential for determination of treatment regimen for these diseases, making accurate and early diagnosis critical. Here we investigate the potential of epigenetic profiles of lung adenocarcinoma, mesothelioma, and non-malignant pulmonary tissues (n=285) as differentiation markers in an analysis of DNA methylation at 1413 autosomal CpG loci associated with 773 cancer-related genes. Using an unsupervised recursively-partitioned mixture modeling technique for all samples, the derived methylation profile classes were significantly associated with sample type (P < 0.0001). In a similar analysis restricted to tumors, methylation profile classes significantly predicted tumor type (P < 0.0001). Random forests classification of CpG methylation of tumors - which splits the data into training and test sets - accurately differentiated MPM from lung adenocarcinoma over 99% of the time (P < 0.0001). In a locus-by-locus comparison of CpG methylation between tumor types, 1266 CpG loci had significantly different methylation between tumors following correction for multiple comparisons (Q < 0.05); 61% had higher methylation in adenocarcinoma. Using the CpG loci with significant differential methylation in a pathways analysis revealed significant enrichment of methylated gene-loci in Cell Cycle Regulation, DNA Damage Response, PTEN Signaling, and Apoptosis Signaling pathways in lung adenocarcinoma when compared to mesothelioma. Methylation-profile-based differentiation of lung adenocarcinoma and mesothelioma is highly accurate, informs on the distinct etiologies of these diseases, and holds promise for clinical application.
Although tumor size and lymph node involvement are the current cornerstones of breast cancer prognosis, they have not been extensively explored in relation to tumor methylation attributes in conjunction with other tumor and patient dietary and hormonal characteristics. Using primary breast tumors from 162 (AJCC stage I–IV) women from the Kaiser Division of Research Pathways Study and the Illumina GoldenGate methylation bead-array platform, we measured 1,413 autosomal CpG loci associated with 773 cancer-related genes and validated select CpG loci with Sequenom EpiTYPER. Tumor grade, size, estrogen and progesterone receptor status, and triple negative status were significantly (Q-values <0.05) associated with altered methylation of 209, 74, 183, 69, and 130 loci, respectively. Unsupervised clustering, using a recursively partitioned mixture model (RPMM), of all autosomal CpG loci revealed eight distinct methylation classes. Methylation class membership was significantly associated with patient race (P<0.02) and tumor size (P<0.001) in univariate tests. Using multinomial logistic regression to adjust for potential confounders, patient age and tumor size, as well as known disease risk factors of alcohol intake and total dietary folate, were all significantly (P<0.0001) associated with methylation class membership. Breast cancer prognostic characteristics and risk-related exposures appear to be associated with gene-specific tumor methylation, as well as overall methylation patterns.
The current standard prognostic indicator for breast cancer is tumor-node-metastasis staging; though, as population-based studies and clinical trials are conducted, molecular characterization of disease is beginning to allow improved markers of prognosis and assist clinicians in choosing the most appropriate therapies. We investigated DNA methylation profiles in over 160 well annotated breast tumor samples and found significant relationships with standard and other known predictors of prognosis, as well as established risk factors for disease: alcohol intake and dietary folate. Recently the United States National Cancer Institute Cancer Biomarkers Research Group articulated a need for a “Strategic Approach to Validating Methylated Genes as Biomarkers for Breast Cancer,” and our work is extremely responsive to this call for a national strategy. Recognizing the increasing use of pre-operative chemotherapy for patients with operable, early-stage disease, there is added complexity in breast cancer staging. Since chemotherapy can considerably decrease tumor size, it is still unclear whether pre-operative or post-operative stage best informs prognosis and treatment decisions for patients electing pre-operative chemotherapy. However, our data clearly illustrate the promise of tumor DNA methylation for augmenting tumor staging and can be attained with minimal tissue in a pre-operative context.
Head and neck squamous cell carcinomas (HNSCCs) represent clinically and etiologically heterogeneous tumors affecting >40 000 patients per year in the USA. Previous research has identified individual epigenetic alterations and, in some cases, the relationship of these alterations with carcinogen exposure or patient outcomes, suggesting that specific exposures give rise to specific types of molecular alterations in HNSCCs. Here, we describe how different etiologic factors are reflected in the molecular character and clinical outcome of these tumors. In a case series of primary, incident HNSCC (n = 68), we examined the DNA methylation profile of 1413 autosomal CpG loci in 773 genes, in relation to exposures and etiologic factors. The overall pattern of epigenetic alteration could significantly distinguish tumor from normal head and neck epithelial tissues (P < 0.0001) more effectively than specific gene methylation events. Among tumors, there were significant associations between specific DNA methylation profile classes and tobacco smoking and alcohol exposures. Although there was a significant association between methylation profile and tumor stage (P < 0.01), we did not observe an association between these profiles and overall patient survival after adjustment for stage; although methylation of a number of specific loci falling in different cellular pathways was associated with overall patient survival. We found that the etiologic heterogeneity of HNSCC is reflected in specific patterns of molecular epigenetic alterations within the tumors and that the DNA methylation profiles may hold clinical promise worthy of further study.
Mechanisms of action of non-mutagenic carcinogens such as asbestos remain poorly characterized. As pleural mesothelioma is known to have limited numbers of genetic mutations, we aimed to characterize the relationships among gene-locus specific methylation alterations, disease status, asbestos burden, and survival in this rapidly-fatal asbestos-associated tumor. Methylation of 1505 CpG loci associated with 803 cancer-related genes were studied in 158 pleural mesotheliomas and 18 normal pleura. After false-discovery rate correction, 969 CpG loci were independently associated with disease status (Q < 0.05). Classifying samples based upon CpG methylation profile with a mixture model approach, methylation classes discriminated tumor from normal pleura (permutation P < 0.0001). In a random forests classification the overall misclassification error rate was 3.4%, with <1% (n=1) of tumors misclassified as normal (P < 0.0001). Among tumors, methylation class membership was significantly associated with lung tissue asbestos body burden (P < 0.03), and significantly predicted survival (likelihood ratio P < 0.01). Consistent with prior work, asbestos burden was associated with an increased risk of death (HR = 1.4, 95% CI, 1.1 – 1.8). Our results have shown that methylation profiles powerfully differentiate diseased pleura from non-tumor pleura and that asbestos burden and methylation profiles are independent predictors of mesothelioma patient survival. We have added to the growing body of evidence that cellular epigenetic dysregulation is a critical mode of action for asbestos in the induction of pleural mesothelioma. Importantly, these findings hold great promise for using epigenetic profiling in the diagnosis and prognosis of human cancers.
Methylation; asbestos; mesothelioma
Epigenetic control of gene transcription is critical for normal human development and cellular differentiation. While alterations of epigenetic marks such as DNA methylation have been linked to cancers and many other human diseases, interindividual epigenetic variations in normal tissues due to aging, environmental factors, or innate susceptibility are poorly characterized. The plasticity, tissue-specific nature, and variability of gene expression are related to epigenomic states that vary across individuals. Thus, population-based investigations are needed to further our understanding of the fundamental dynamics of normal individual epigenomes. We analyzed 217 non-pathologic human tissues from 10 anatomic sites at 1,413 autosomal CpG loci associated with 773 genes to investigate tissue-specific differences in DNA methylation and to discern how aging and exposures contribute to normal variation in methylation. Methylation profile classes derived from unsupervised modeling were significantly associated with age (P<0.0001) and were significant predictors of tissue origin (P<0.0001). In solid tissues (n = 119) we found striking, highly significant CpG island–dependent correlations between age and methylation; loci in CpG islands gained methylation with age, loci not in CpG islands lost methylation with age (P<0.001), and this pattern was consistent across tissues and in an analysis of blood-derived DNA. Our data clearly demonstrate age- and exposure-related differences in tissue-specific methylation and significant age-associated methylation patterns which are CpG island context-dependent. This work provides novel insight into the role of aging and the environment in susceptibility to diseases such as cancer and critically informs the field of epigenomics by providing evidence of epigenetic dysregulation by age-related methylation alterations. Collectively we reveal key issues to consider both in the construction of reference and disease-related epigenomes and in the interpretation of potentially pathologically important alterations.
The causes and extent of tissue-specific interindividual variation in human epigenomes are underappreciated and, hence, poorly characterized. We surveyed over 200 carefully annotated human tissue samples from ten anatosites at 1,413 CpGs for methylation alterations to appraise the nature of phenotypically, and hence potentially clinically important epigenomic alterations. Within tissue types, across individuals, we found variation in methylation that was significantly related to aging and environmental exposures such as tobacco smoking. Individual variation in age- and exposure-related methylation may significantly contribute to increased susceptibility to several diseases. As the NIH–funded HapMap project is critically contributing to annotating the human reference genome defining normal genetic variability, our work raises key issues to consider in the construction of reference epigenomes. It is well recognized that understanding genetic variation is essential to understanding disease. Our work, and the known interplay of epigenetics and genetics, makes it equally clear that a more complete characterization of epigenetic variation and its sources must be accomplished to reach the goal of a complete understanding of disease. Additional research is absolutely necessary to define the mechanisms controlling epigenomic variation. We have begun to lay the foundations for essential normal tissue controls for comparison to diseased tissue, which will allow the identification of the most crucial disease-related alterations and provide more robust targets for novel treatments.
Arsenic (As), a ubiquitous environmental toxicant, has recently been linked to disrupted immune function and enhanced infection susceptibility in highly exposed populations. Drinking water As levels above the EPA maximum contaminant level occur in our US study area and are a particular health concern for pregnant women and infants. As part of the New Hampshire Birth Cohort Study, we investigated whether in utero exposure to As affects risk of infant infections. We prospectively obtained information on four-month-old infants (n=214) using a parental telephone survey on infant’s infections and symptoms, including respiratory infections, diarrhea and specific illnesses, as well as the duration and severity of infections. Using logistic regression and Poisson models, we evaluated the association between maternal urinary As during pregnancy and infection risks adjusted for potentially confounding factors. Maternal urinary As concentrations were related to total number of infections requiring a physician visit (Relative Risk (RR) per one-fold increase in As in urine =1.5; 95% confidence interval (CI)=1.0, 2.1) or prescription medication (RR=1.6; 95% CI =1.1, 2.4), as well as lower respiratory infections treated with prescription medication (RR=3.3; 95% CI =1.2, 9.0). Associations were observed with respiratory symptoms (RR=4.0; 95% CI =1.0, 15.8), upper respiratory infections (RR=1.6; 95% CI =1.0, 2.5), and colds treated with prescription medication (RR=2.3; 95% CI =1.0, 5.2). Our results provide initial evidence that in utero As exposure may be related to infant infection and infection severity and provide insight into the early life impacts of fetal As exposure.
Arsenic; infant respiratory infection; prenatal exposure; pregnancy; US cohort
A growing body of evidence suggests that in utero and early-life exposure to arsenic may have detrimental effects on children, even at the low to moderate levels common in the United States and elsewhere. In a sample of 170 mother–infant pairs from New Hampshire, we determined infant exposure to in utero arsenic by evaluating infant toenails as a biomarker using inductively coupled plasma mass spectrometry. Infant toenail arsenic concentration correlated with maternal postpartum toenail concentrations (Spearman’s correlation coefficient 0.34). In adjusted linear models, a doubling of maternal toenail arsenic concentration was associated with a 53.8% increase in infant toenail arsenic concentration as compared with 20.4% for a doubling of maternal urine arsenic concentration. In a structural equation model, a doubling of the latent variable integrating maternal toenail and urine arsenic concentrations was associated with a 67.5% increase in infant toenail arsenic concentration. A similar correlation between infant and maternal postpartum toenail concentrations was observed in a validation cohort of 130 mother–infant pairs from Rhode Island. In utero exposure to arsenic occurs through maternal water and dietary sources, and infant toenails appear to be a reliable biomarker for estimating arsenic exposure during the critical window of gestation.
biological markers; biomarkers; arsenic; prenatal exposure
Indoor and outdoor air pollution is known to contribute to increased lung cancer incidence. This study is the first to address the contribution of home heating fuel and geographical course particulate matter (PM10) concentrations to lung cancer rates in New Hampshire, U.S. First, Pearson correlation analysis and Geographically weighted regression were used to investigate spatial relationships between outdoor PM10 and lung cancer rates. While the aforementioned analyses did not indicate a significant contribution of PM10 to lung cancer in the state, there was a trend towards a significant association in the northern and southwestern regions of the state. Second, case-control data were used to estimate the contributions of indoor pollution and second hand smoke to risk of lung cancer with adjustment for confounders. Increased risk was found among those who used wood or coal to heat their homes for more than 10 winters before the age of 18, with a significant increase in risk per winter. Resulting data suggest that further investigation of the relationship between heating-related air pollution levels and lung cancer risk is needed.
Arsenic is associated with bladder cancer risk even at low exposure levels. Genetic variation in enzymes involved in xenobiotic and arsenic metabolism may modulate individual susceptibility to arsenic-related bladder cancer. Through a population-based case-control study in NH (832 cases and 1191 controls), we investigated gene-environment interactions between arsenic metabolic gene polymorphisms and arsenic exposure in relation to bladder cancer risk. Toenail arsenic concentrations were used to classify subjects into low and high exposure groups. Single nucleotide polymorphisms (SNPs) in GSTP1, GSTO2, GSTZ1, AQP3, AS3MT and the deletion status of GSTM1 and GSTT1 were determined. We found evidence of genotype-arsenic interactions in the high exposure group; GSTP1 Ile105Val homozygous individuals had an odds ratio (OR) of 5.4 [95% confidence interval (CI): 1.5-20.2; P for interaction = 0.03] and AQP3 Phe130Phe carriers had an OR=2.2 (95% CI: 0.8-6.1; P for interaction = 0.10). Bladder cancer risk overall was associated with GSTO2 Asn142Asp (homozygous; OR=1.4; 95% CI: 1.0-1.9; P for trend=0.06) and GSTZ1 Glu32Lys (homozygous; OR=1.3; 95%CI: 0.9-1.8; P for trend=0.06). Our findings suggest that susceptibility to bladder cancer may relate to variation in genes involved in arsenic metabolism and oxidative stress response and potential gene-environment interactions requiring confirmation in other populations.
arsenic; genetic polymorphisms; bladder cancer; case-control study; gene-environment interaction
Oral contraceptives (OCs) affect the risk of several cancers in women, but have been virtually unstudied for squamous cell carcinoma (SCC). We examined the hypothesis that OCs influence SCC risk in a case–control study among women and also examined whether polymorphisms in the DNA repair gene, Xeroderma pigmentosum group D (XPD), modified the risk. Incident cases of SCC were identified by a network of dermatologists and pathology laboratories. Population-based controls were frequency matched to cases by age and gender (n = 261 SCC cases, 298 controls). Overall, OC use was associated with a 60% higher risk of SCC (odds ratio (OR), 1.6; 95% confidence interval (95% CI): 1.0–2.5). ORs for SCC were higher among those who last used OCs ≥25 years before diagnosis (OR: 2.1; 95% CI: 1.2–3.7), and among these women, SCC risk increased with duration of use (OR for ≤2 years, 1.7; 95% CI: 0.9–3.5; OR for 3–6 years, 2.6; 95% CI: 1.0–6.5; OR for ≥7 years, 2.7; 95% CI: 0.9–8.5, Ptrend = 0.01). Furthermore, the XPD Lys751Gln polymorphism was a significant modifier of the OC-SCC association (Pinteraction = 0.03). These findings lead us to hypothesize a potential relationship between OCs and SCC risk, and that this could involve DNA repair pathways.
Emerging evidence indicates a potential role of selenium in the prevention of several types of cancer, including bladder cancer. We investigated the association between toenail selenium concentrations and bladder cancer risk in a population-based case-control study in New Hampshire. We analyzed data from 857 incidence cases diagnosed between July 1, 1994 and June 30, 2001 and 1,191 general population controls. Newly diagnosed cases of bladder cancer were identified from the New Hampshire State Cancer Registry, which operates a rapid reporting system. Controls were selected from population lists (driver's license and Medicare enrollment). We used logistic regression analyses to generate odds ratios (OR) and 95% confidence intervals (95% CI), controlling for age, sex, and pack-years of smoking and conducted separate analyses according to the intensity of p53 immunohistochemical staining of the tumor. Overall, toenail selenium concentrations were not significantly related to bladder cancer [OR Q4 versus Q1, 0.90 (95% CI, 0.68−1.19); Ptrend = 0.15]. However, within specific subgroups there were inverse associations, i.e., among moderate smokers [OR, 0.61 (95% CI, 0.39−0.96); Ptrend = 0.004], women [OR, 0.66 (95% CI, 0.40−1.10); Ptrend = 0.11], and those with p53-positive cancers [OR Q4 versus Q1, 0.57 (95% CI, 0.34−0.94); Ptrend = 0.01]. Our results indicate that seleniumis not inversely related to risk of bladder cancer overall; however, they raise the possibility that selenium may be preventive in certain molecular phenotypes of tumors (e.g., p53 positive) or within certain subsets of a population (e.g., women or moderate smokers).
Several different genetic and environmental factors have been identified as independent risk factors for bladder cancer in population-based studies. Recent studies have turned to understanding the role of gene-gene and gene-environment interactions in determining risk. We previously developed the bioinformatics framework of statistical epistasis networks (SEN) to characterize the global structure of interacting genetic factors associated with a particular disease or clinical outcome. By applying SEN to a population-based study of bladder cancer among Caucasians in New Hampshire, we were able to identify a set of connected genetic factors with strong and significant interaction effects on bladder cancer susceptibility.
To support our statistical findings using networks, in the present study, we performed pathway enrichment analyses on the set of genes identified using SEN, and found that they are associated with the carcinogen benzo[a]pyrene, a component of tobacco smoke. We further carried out an mRNA expression microarray experiment to validate statistical genetic interactions, and to determine if the set of genes identified in the SEN were differentially expressed in a normal bladder cell line and a bladder cancer cell line in the presence or absence of benzo[a]pyrene. Significant nonrandom sets of genes from the SEN were found to be differentially expressed in response to benzo[a]pyrene in both the normal bladder cells and the bladder cancer cells. In addition, the patterns of gene expression were significantly different between these two cell types.
The enrichment analyses and the gene expression microarray results support the idea that SEN analysis of bladder in population-based studies is able to identify biologically meaningful statistical patterns. These results bring us a step closer to a systems genetic approach to understanding cancer susceptibility that integrates population and laboratory-based studies.
Epistasis; Gene-gene interactions; Statistical epistasis networks; Benzo[a]pyrene; Gene-drug association; Bladder cancer
Skin cancer survivors experience an increased risk for subsequent malignancies but the associated risk factors are poorly understood. This study examined the risk of a new primary cancer following an initial skin cancer and assessed risk factors associated with second primary cancers.
All invasive cutaneous malignant melanomas (CMM, N = 28 069) and squamous cell carcinomas (SCC, N = 24 620) diagnosed in Norway during 1955–2008 were included. Rates of new primary cancers in skin cancer survivors were compared to rates of primary malignancies in the general population using standardized incidence ratios (SIR). Discrete-time logistic regression models were applied to individual-level data to estimate cancer risk among those with and without a prior skin cancer, accounting for residential region, education, income, parenthood, marital status and parental cancer status, using a 20% random sample of the entire Norwegian population as reference. Further analyses of the skin cancer cohort were undertaken to determine risk factors related to subsequent cancers.
During follow-up, 9608 new primary cancers occurred after an initial skin cancer. SIR analyses showed 50% and 90% increased risks for any cancer after CMM and SCC, respectively (p < 0.01). The logistic regression model suggested even stronger increase after SCC (130%). The highest risk was seen for subsequent skin cancers, but several non-skin cancers were also diagnosed in excess: oral, lung, colon, breast, prostate, thyroid, leukemia, lymphoma and central nervous system. Factors that were associated with increased risk of subsequent cancers include male sex, older age, lower residential latitude, being married and low education and income. Parental cancer did not increase the risk of a subsequent cancer after SCC, but was a significant predictor among younger CMM survivors.
Our results provide information on shared environmental and genetic risk factors for first and later cancers and may help to identify individuals at high risk for subsequent cancers, which will be important as skin cancer incidence continues to rise.
Malignant Melanoma; Squamous Cell Carcinoma; Second cancer; Population-based; Sociodemographic factors; Family
It is well-known that ultraviolet (UV) light exposure and a sun sensitive phenotype are risk factors for the development of non-melanoma skin cancer (NMSC), including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). In this New Hampshire population-based case-control study, we collected data from 5,072 individuals, including histologically-confirmed cases of BCC and SCC, and controls via a personal interview to investigate possible associations between photosensitizing medication use and NMSC. After adjustment for potentially confounding factors (e.g. lifetime number of painful sunburns), we found a modest increase in risk of SCC (OR = 1.2, 95% CI = 1.0–1.4) and BCC (OR = 1.2, 95% CI = 0.9–1.5), in particular early-onset BCC, (≤ 50 years of age) (OR = 1.5, 95% CI = 1.1–2.1) associated with photosensitizing medication use. For SCC the association was strongest amongst those with tendency to sunburn rather than tan. We also specifically found associations with BCC, and especially early-onset BCC, and photosensitizing antimicrobials. In conclusion, certain commonly prescribed photosensitizing medications may enhance the risk of developing SCC, especially in individuals with a sun sensitive phenotype, and may increase the risk of developing BCC and incidence of BCC at a younger age.
Limited data exist on the contribution of dietary sources of arsenic to an individual’s total exposure, particularly in populations with exposure via drinking water. Here, the association between diet and toenail arsenic concentrations (a long-term biomarker of exposure) was evaluated for individuals with measured household tap water arsenic. Foods known to be high in arsenic, including rice and seafood, were of particular interest.
Associations between toenail arsenic and consumption of 120 individual diet items were quantified using general linear models that also accounted for household tap water arsenic and potentially confounding factors (e.g., age, caloric intake, sex, smoking) (n = 852). As part of the analysis, we assessed whether associations between log-transformed toenail arsenic and each diet item differed between subjects with household drinking water arsenic concentrations <1 μg/L versus ≥1 μg/L.
As expected, toenail arsenic concentrations increased with household water arsenic concentrations. Among the foods known to be high in arsenic, no clear relationship between toenail arsenic and rice consumption was detected, but there was a positive association with consumption of dark meat fish, a category that includes tuna steaks, mackerel, salmon, sardines, bluefish, and swordfish. Positive associations between toenail arsenic and consumption of white wine, beer, and Brussels sprouts were also observed; these and most other associations were not modified by exposure via water. However, consumption of two foods cooked in water, beans/lentils and cooked oatmeal, was more strongly related to toenail arsenic among those with arsenic-containing drinking water (≥1 μg/L).
This study suggests that diet can be an important contributor to total arsenic exposure in U.S. populations regardless of arsenic concentrations in drinking water. Thus, dietary exposure to arsenic in the US warrants consideration as a potential health risk.
Biomarkers; Drinking water; Population-based study; Food borne exposure; Rice; Fish
Most human exposure to mercury (Hg) in the United States is from consuming marine fish and shellfish. The Gulf of Maine is a complex marine ecosystem comprised of twelve physioregions, including the Bay of Fundy, coastal shelf areas and deeper basins that contain highly productive fishing grounds. Here we review available data on spatial and temporal Hg trends to better understand the drivers of human and biological exposures. Atmospheric Hg deposition from U.S. and Canadian sources has declined since the mid-1990s in concert with emissions reductions but deposition from global sources has increased. Oceanographic circulation is the dominant source of total Hg inputs to the entire Gulf of Maine region (59%), followed by atmospheric deposition (28%), wastewater/industrial sources (8%), and rivers (5%). Resuspension of sediments increases MeHg inputs to overlying waters raising concerns about benthic trawling activities in shelf regions. In the near coastal areas, elevated sediment and mussel Hg levels are co-located in urban embayments and near large historical point sources. Temporal patterns in sentinel species (mussels and birds) have in some cases declined in response to localized point source mercury reductions but overall Hg trends do not show consistent declines. For example, levels of Hg have either declined or remained stable in eggs from four seabird species collected in the Bay of Fundy since 1972. Quantitatively linking Hg exposures from fish harvested from the Gulf of Maine to human health risks is challenging at this time because no data are available on the geographic origin of seafood consumed by coastal residents. In addition, there is virtually no information on Hg levels in commercial species for offshore regions of the Gulf of Maine where some of the most productive fisheries are located. Both of these data gaps should be priorities for future research.
Gulf of Maine; North Atlantic; methylmercury; fish; risk
We review the applicability of Bayesian networks (BNs) for discovering relations between genes, environment, and disease. By translating probabilistic dependencies among variables into graphical models and vice versa, BNs provide a comprehensible and modular framework for representing complex systems. We first describe the Bayesian network approach and its applicability to understanding the genetic and environmental basis of disease. We then describe a variety of algorithms for learning the structure of a network from observational data. Because of their relevance to real-world applications, the topics of missing data and causal interpretation are emphasized. The BN approach is then exemplified through application to data from a population-based study of bladder cancer in New Hampshire, USA. For didactical purposes, we intentionally keep this example simple. When applied to complete data records, we find only minor differences in the performance and results of different algorithms. Subsequent incorporation of partial records through application of the EM algorithm gives us greater power to detect relations. Allowing for network structures that depart from a strict causal interpretation also enhances our ability to discover complex associations including gene-gene (epistasis) and gene-environment interactions. While BNs are already powerful tools for the genetic dissection of disease and generation of prognostic models, there remain some conceptual and computational challenges. These include the proper handling of continuous variables and unmeasured factors, the explicit incorporation of prior knowledge, and the evaluation and communication of the robustness of substantive conclusions to alternative assumptions and data manifestations.
Structural learning; Belief networks; Genetic epidemiology; Bioinformatics; Complex traits; Arsenic; SNP
tattoo; health behavior survey; women’s health
Background: In adult populations, emerging evidence indicates that humans are exposed to arsenic by ingestion of contaminated foods such as rice, grains, and juice; yet little is known about arsenic exposure among children.
Objectives: Our goal was to determine whether rice consumption contributes to arsenic exposure in U.S. children.
Methods: We used data from the nationally representative National Health and Nutrition Examination Survey (NHANES) to examine the relationship between rice consumption (measured in 0.25 cups of cooked rice per day) over a 24-hr period and subsequent urinary arsenic concentration among the 2,323 children (6–17 years of age) who participated in NHANES from 2003 to 2008. We examined total urinary arsenic (excluding arsenobetaine and arsenocholine) and dimethylarsinic acid (DMA) concentrations overall and by age group: 6–11 years and 12–17 years.
Results: The median [interquartile range (IQR)] total urinary arsenic concentration among children who reported consuming rice was 8.9 μg/L (IQR: 5.3–15.6) compared with 5.5 μg/L (IQR: 3.1–8.4) among those who did not consume rice. After adjusting for potentially confounding factors, and restricting the study to participants who did not consume seafood in the preceding 24 hr, total urinary arsenic concentration increased 14.2% (95% confidence interval: 11.3, 17.1%) with each 0.25 cup increase in cooked rice consumption.
Conclusions: Our study suggests that rice consumption is a potential source of arsenic exposure in U.S. children.
arsenic; biomonitoring; children; dietary; exposure; NHANES
Aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) are potentially chemopreventive.
We examined the relation between NSAID use and non-melanoma skin cancer in a population-based case-control study.
NSAID and analgesic use was analyzed in 1484 subjects: 535 squamous cell carcinoma (SCC), 487 basal cell carcinoma (BCC), and 462 controls.
Use of NSAIDs, particularly aspirin, related to reduced odds ratios (OR) of SCC especially tumors positive for p53 (OR = 0.29; 95% CI= 0.11-0.79) or with PTCH loss of heterozygosity (OR = 0.35; 95% CI = 0.13 – 0.96). Although not considered an NSAID, decreased odds ratios of both BCC and SCC were observed in relation to use of paracetamol. Risk of BCC was unrelated to NSAID use.
Self reported drug use.
This study supports the hypothesis that NSAIDs, aspirin in particular, may reduce risk of SCC and additionally may affect specific molecular subtypes of SCC.
NSAIDS; non-melanoma skin cancer; basal cell carcinoma; squamous cell carcinoma; p53; PTCH; case-control study