Kimberly D. Siegmund

Association of Breast Cancer DNA Methylation Profiles with Hormone Receptor Status and Response to Tamoxifen

We have generated DNA methylation profiles of 148 human breast tumors and found significant differences in hormone receptor (HR) status between clusters of DNA methylation profiles. Of 35 DNA methylation markers analyzed, the ESR1 gene, encoding estrogen receptor α, proved to be the best predictor of progesterone receptor status, whereas methylation of the PGR gene, encoding progesterone receptor, was the best predictor of estrogen receptor status. ESR1 methylation outperformed HR status as a predictor of clinical response in patients treated with the antiestrogen tamoxifen, whereas promoter methylation of the CYP1B1 gene, encoding a tamoxifen- and estradiol-metabolizing cytochrome P450, predicted response differentially in tamoxifen-treated and nontamoxifen-treated patients. High levels of promoter methylation of the ARHI gene, encoding a RAS-related small G-protein, were strongly predictive of good survival in patients who had not received tamoxifen therapy. Our results reveal an as yet unrecognized degree of interaction between DNA methylation and HR biology in breast cancer cells and suggest potentially clinically useful novel DNA methylation predictors of response to hormonal and non-hormonal breast cancer therapy.

Recommendations for the design and analysis of epigenome-wide association studies

Epigenome-wide association studies (EWAS) hold promise for the detection of new regulatory mechanisms that may be susceptible to modification by environmental and lifestyle factors affecting susceptibility to disease. Epigenome-wide screening methods cover an increasing number of CpG sites, but the complexity of the data poses a challenge to separating robust signals from noise. Appropriate study design, a detailed a priori analysis plan and validation of results are essential to minimize the danger of false positive results and contribute to a unified approach. Epigenome-wide mapping studies in homogenous cell populations will inform our understanding of normal variation in the methylome that is not associated with disease or aging. Here we review concepts for conducting a stringent and powerful EWAS, including the choice of analyzed tissue, sources of variability and systematic biases, outline analytical solutions to EWAS-specific problems and highlight caveats in interpretation of data generated from samples with cellular heterogeneity.

Detection of methylated apoptosis-associated genes in urine sediments of bladder cancer patients.

Purpose: There is increasing evidence for a fundamental role for epigenetic silencing of apoptotic pathways in cancer. Changes in DNA methylation can be detected with a high degree of sensitivity, so we used the MethyLight assay to determine how methylation patterns of apoptosis-associated genes change during bladder carcinogenesis and whether DNA methylation could be detected in urine sediments. Experimental Design: We analyzed the methylation status of the 5′ regions of 12 apoptosis-associated genes (ARF, FADD, TNFRSF21, BAX, LITAF, DAPK, TMS-1, BCL2, RASSF1A, TERT, TNFRSF25, and EDNRB) in 18 bladder cancer cell lines, 127 bladder cancer samples, and 37 samples of adjacent normal bladder mucosa using the quantitative MethyLight assay. We also analyzed the methylation status in urine sediments of 20 cancer-free volunteers and 37 bladder cancer patients. Results: The 5′ regions of DAPK, BCL2, TERT, RASSFIA, and TNFRSF25 showed significant increases in methylation levels when compared with nonmalignant adjacent tissue (P ≤ 0.01). Methylation levels of BCL2 were significantly associated with tumor staging and grading (P ≤ 0.01), whereas methylation levels of RASSF1A and ARF were only associated with tumor stage (P ≤ 0.04), and TERT methylation and EDNRB methylation were predictors of tumor grade (P ≤ 0.02). To investigate clinical usefulness for noninvasive bladder cancer detection, we further analyzed the methylation status of the markers in urine samples of patients with bladder cancer. Methylation of DAPK, BCL2, and TERT in urine sediment DNA from bladder cancer patients was detected in the majority of samples (78%), whereas they were unmethylated in the urine sediment DNA from age-matched cancer-free individuals. Conclusions: Our results indicate that methylation of the 5′ region of apoptosis-associated genes is a common finding in patients with bladder carcinoma. The ability to detect methylation not only in bladder tissue, but also in urine sediments, suggests that methylation markers are promising tools for noninvasive detection of bladder cancers. Our results also indicate that some methylation markers, such as those in regions of RASSF1A and TNFRSF25, might be of limited use for detection because they are also methylated in normal bladder tissues.

Epigenetic profiling of somatic tissues from human autopsy specimens identifies tissue- and individual-specific DNA methylation patterns

DNA methylation is known to be associated with cell differentiation, aging, disease and cancer. There exists an expanding base of knowledge regarding tissue-specific DNA methylation, but we have little information about person-specific DNA methylation. Here, we analyze the DNA methylation patterns of multiple tissues from multiple individuals using a high-throughput quantitative assay of genome-wide DNA methylation, namely the Illumina GoldenGate BeadArray. DNA methylation patterns were largely conserved across 11 different tissues (r = 0.852) and across six individuals (r = 0.829), and we found that DNA was highly methylated in non-CpG islands and/or CpG sites that are not occupied by either H3K4me3 or H3K27me3 (P < 0.05). Finally, we found that the Illumina GoldenGate assay features a large number of probes (265/1505 probes, 17.6%) that contain single-nucleotide polymorphisms, which may interfere with DNA methylation analyses in genome-wide studies.

Environmental epigenetics: prospects for studying epigenetic mediation of exposure–response relationships

Changes in epigenetic marks such as DNA methylation and histone acetylation are associated with a broad range of disease traits, including cancer, asthma, metabolic disorders, and various reproductive conditions. It seems plausible that changes in epigenetic state may be induced by environmental exposures such as malnutrition, tobacco smoke, air pollutants, metals, organic chemicals, other sources of oxidative stress, and the microbiome, particularly if the exposure occurs during key periods of development. Thus, epigenetic changes could represent an important pathway by which environmental factors influence disease risks, both within individuals and across generations. We discuss some of the challenges in studying epigenetic mediation of pathogenesis and describe some unique opportunities for exploring these phenomena.

Hypomethylation of a LINE-1 Promoter Activates an Alternate Transcript of the MET Oncogene in Bladders with Cancer

It was recently shown that a large portion of the human transcriptome can originate from within repetitive elements, leading to ectopic expression of protein-coding genes. However the mechanism of transcriptional activation of repetitive elements has not been definitively elucidated. For the first time, we directly demonstrate that hypomethylation of retrotransposons can cause altered gene expression in humans. We also reveal that active LINE-1s switch from a tetranucleosome to dinucleosome structure, acquiring H2A.Z- and nucleosome-free regions upstream of TSSs, previously shown only at active single-copy genes. Hypomethylation of a specific LINE-1 promoter was also found to induce an alternate transcript of the MET oncogene in bladder tumors and across the entire urothelium of tumor-bearing bladders. These data show that, in addition to contributing to chromosomal instability, hypomethylation of LINE-1s can alter the functional transcriptome and plays a role not only in human disease but also in disease predisposition.

Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression.

Lung cancer is the leading cause of cancer death worldwide, and adenocarcinoma is its most common histological subtype. Clinical and molecular evidence indicates that lung adenocarcinoma is a heterogeneous disease, which has important implications for treatment. Here we performed genome-scale DNA methylation profiling using the Illumina Infinium HumanMethylation27 platform on 59 matched lung adenocarcinoma/non-tumor lung pairs, with genome-scale verification on an independent set of tissues. We identified 766 genes showing altered DNA methylation between tumors and non-tumor lung. By integrating DNA methylation and mRNA expression data, we identified 164 hypermethylated genes showing concurrent down-regulation, and 57 hypomethylated genes showing increased expression. Integrated pathways analysis indicates that these genes are involved in cell differentiation, epithelial to mesenchymal transition, RAS and WNT signaling pathways, and cell cycle regulation, among others. Comparison of DNA methylation profiles between lung adenocarcinomas of current and never-smokers showed modest differences, identifying only LGALS4 as significantly hypermethylated and down-regulated in smokers. LGALS4, encoding a galactoside-binding protein involved in cell-cell and cell-matrix interactions, was recently shown to be a tumor suppressor in colorectal cancer. Unsupervised analysis of the DNA methylation data identified two tumor subgroups, one of which showed increased DNA methylation and was significantly associated with KRAS mutation and to a lesser extent, with smoking. Our analysis lays the groundwork for further molecular studies of lung adenocarcinoma by identifying novel epigenetically deregulated genes potentially involved in lung adenocarcinoma development/progression, and by describing an epigenetic subgroup of lung adenocarcinoma associated with characteristic molecular alterations.

Low-level processing of Illumina Infinium DNA Methylation BeadArrays.

We propose a novel approach to background correction for Infinium HumanMethylation data to account for technical variation in background fluorescence signal. Our approach capitalizes on a new use for the Infinium I design bead types to measure non-specific fluorescence in the colour channel opposite of their design (Cy3/Cy5). This provides tens of thousands of features for measuring background instead of the much smaller number of negative control probes on the platforms (n = 32 for HumanMethylation27 and n = 614 for HumanMethylation450, respectively). We compare the performance of our methods with existing approaches, using technical replicates of both mixture samples and biological samples, and demonstrate that within- and between-platform artefacts can be substantially reduced, with concomitant improvement in sensitivity, by the proposed methods.

Molecular Characterization of MSI-H Colorectal Cancer by MLHI Promoter Methylation, Immunohistochemistry, and Mismatch Repair Germline Mutation Screening

Microsatellite instability (MSI) occurs in 10% to 20% of colorectal cancers (CRC) and has been attributed to both MLH1 promoter hypermethylation and germline mutation in the mismatch repair (MMR) genes. We present results from a large population- and clinic-based study of MLH1 methylation, immunohistochemistry, and MMR germline mutations that enabled us to (a) estimate the prevalence of MMR germline mutations and MLH1 methylation among MSI-H cases and help us understand if all MSI-H CRC is explained by these mechanisms and (b) estimate the associations between MLH1 methylation and sex, age, and tumor location within the colon. MLH1 methylation was measured in 1,061 population-based and 172 clinic-based cases of CRC. Overall, we observed MLH1 methylation in 60% of population-based MSI-H cases and in 13% of clinic-based MSI-H cases. Within the population-based cases with MMR mutation screening and conclusive immunohistochemistry results, we identified a molecular event in MMR in 91% of MSI-H cases: 54% had MLH1 methylation, 14% had a germline mutation in a MMR gene, and 23% had immunohistochemistry evidence for loss of a MMR protein. We observed a striking age difference, with the prevalence of a MMR germline mutation more than 4-fold lower and the prevalence of MLH1 methylation more than 4-fold higher in cases diagnosed after the age of 50 years than in cases diagnosed before that age. We also determined that female sex is an independent predictor of MLH1 methylation within the MSI-H subgroup. These results reinforce the importance of distinguishing between the underlying causes of MSI in studies of etiology and prognosis. (Cancer Epidemiol Biomarkers Prev 2008;17(11):3208–15)

The PREMM1,2,6 Model Predicts Risk of MLH1, MSH2, and MSH6 Germline Mutations Based on Cancer History

BACKGROUND & AIMS We developed and validated a model to estimate the risks of mutations in the mismatch repair (MMR) genes MLH1, MSH2, and MSH6 based on personal and family history of cancer. METHODS Data were analyzed from 4539 probands tested for mutations in MLH1, MSH2, and MSH6. A multivariable polytomous logistic regression model (PREMM(1,2,6)) was developed to predict the overall risk of MMR gene mutations and the risk of mutation in each of the 3 genes. The discriminative ability of the model was validated in 1827 population-based colorectal cancer (CRC) cases. RESULTS Twelve percent of the original cohort carried pathogenic mutations (204 in MLH1, 250 in MSH2, and 71 in MSH6). The PREMM(1,2,6) model incorporated the following factors from the probands and first- and second-degree relatives (odds ratio; 95% confidence intervals [CIs]): male sex (1.9; 1.5-2.4), a CRC (4.3; 3.3-5.6), multiple CRCs (13.7; 8.5-22), endometrial cancer (6.1; 4.6-8.2), and extracolonic cancers (3.3; 2.4-4.6). The areas under the receiver operating characteristic curves were 0.86 (95% CI, 0.82-0.91) for MLH1 mutation carriers, 0.87 (95% CI, 0.83-0.92) for MSH2, and 0.81 (95% CI, 0.69-0.93) for MSH6; in validation, they were 0.88 for the overall cohort (95% CI, 0.86-0.90) and the population-based cases (95% CI, 0.83-0.92). CONCLUSIONS We developed the PREMM(1,2,6) model, which incorporates information on cancer history from probands and their relatives to estimate an individuals risk of mutations in the MMR genes MLH1, MSH2, and MSH6. This Web-based decision making tool can be used to assess risk of hereditary CRC and guide clinical management.