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

Oncoprotein ZNF322A transcriptionally deregulates alpha-adducin, cyclin D1 and p53 to promote tumor growth and metastasis in lung cancer

ZNF322A encoding a classical Cys2His2 zinc finger transcription factor was previously revealed as a potential oncogene in lung cancer patients. However, the oncogenic role of ZNF322A and its underlying mechanism in lung tumorigenesis remain elusive. Here we show ZNF322A protein overexpression in 123 Asian and 74 Caucasian lung cancer patients. Multivariate Cox regression analysis indicated that ZNF322A was an independent risk factor for a poor outcome in lung cancer, corroborating the Kaplan–Meier results that patients with ZNF322A protein overexpression had significantly poorer overall survival than other patients. Overexpression of ZNF322A promoted cell proliferation and soft agar growth by prolonging cell cycle in S phase in multiple lung cell lines, including the immortalized lung cell BEAS-2B. In addition, ZNF322A overexpression enhanced cell migration and invasion, whereas knockdown of ZNF322A reduced cell growth, invasion and metastasis abilities in vitro and in vivo. Quantitative proteomic analysis revealed potential ZNF322A-regulated downstream targets, including alpha-adducin (ADD1), cyclin D1 (CCND1), and p53. Using luciferase promoter activity assay combined with site-directed mutagenesis and sequential chromatin immunoprecipitation-PCR assay, we found that ZNF322A could form a complex with c-Jun and cooperatively activate ADD1 and CCND1 but repress p53 gene transcription by recruiting differential chromatin modifiers, such as histone deacetylase 3, in an AP-1 element dependent manner. Reconstitution experiments indicated that CCND1 and p53 were important to ZNF322A-mediated promotion of cell proliferation, whereas ADD1 was necessary for ZNF322A-mediated cell migration and invasion. Our results provide compelling evidence that ZNF322A overexpression transcriptionally dysregulates genes involved in cell growth and motility therefore contributes to lung tumorigenesis and poor prognosis.

Critical limitations of prognostic signatures based on risk scores summarized from gene expression levels: a case study for resected stage I non-small-cell lung cancer

Most of current gene expression signatures for cancer prognosis are based on risk scores, usually calculated as some summaries of expression levels of the signature genes, whose applications require presetting risk score thresholds and data normalization. In this study, we demonstrate the critical limitations of such type of signatures that the risk scores of samples will change greatly when they are normalized together with different samples, which would induce spurious risk classification and difficulty in clinical settings, and the risk scores of independent samples are incomparable if data normalization is not adopted. To overcome these limitations, we propose a rank-based method to extract a prognostic gene pair signature for overall survival of stage I non-small-cell lung cancer. The prognostic gene pair signature is verified in three integrated data sets detected by different laboratories with different microarray platforms. We conclude that, different from the type of signatures based on risk scores summarized from gene expression levels, the rank-based signatures could be robustly applied at the individualized level to independent clinical samples assessed in different laboratories.

MicroRNA-148a reduces tumorigenesis and increases TRAIL-induced apoptosis in NSCLC

Nonsmall cell lung cancer (NSCLC) is one of the leading causes of death worldwide. TNF-related apoptosis-inducing ligand (TRAIL) has been shown to induce apoptosis in malignant cells without inducing significant toxicity in normal cells. However, several carcinomas, including lung cancer, remain resistant to TRAIL. MicroRNAs (miRNAs) are small noncoding RNAs of ∼ 24 nt that block mRNA translation and/or negatively regulate its stability. They are often aberrantly expressed in cancer and have been implicated in increasing susceptibility or resistance to TRAIL-induced apoptosis by inhibiting key functional proteins. Here we show that miR-148a is down-regulated in cells with acquired TRAIL-resistance compared with TRAIL-sensitive cells. Enforced expression of miR-148a sensitized cells to TRAIL and reduced lung tumorigenesis in vitro and in vivo through the down-modulation of matrix metalloproteinase 15 (MMP15) and Rho-associated kinase 1 (ROCK1). These findings suggest that miR-148a acts as a tumor suppressor and might have therapeutic application in the treatment of NSCLC.

Hidden among the crowd: differential DNA methylation-expression correlations in cancer occur at important oncogenic pathways

DNA methylation is a frequent epigenetic mechanism that participates in transcriptional repression. Variations in DNA methylation with respect to gene expression are constant, and, for unknown reasons, some genes with highly methylated promoters are sometimes overexpressed. In this study we have analyzed the expression and methylation patterns of thousands of genes in five groups of cancer and normal tissue samples in order to determine local and genome-wide differences. We observed significant changes in global methylation-expression correlation in all the neoplasms, which suggests that differential correlation events are frequent in cancer. A focused analysis in the breast cancer cohort identified 1662 genes whose correlation varies significantly between normal and cancerous breast, but whose DNA methylation and gene expression patterns do not change substantially. These genes were enriched in cancer-related pathways and repressive chromatin features across various model cell lines, such as PRC2 binding and H3K27me3 marks. Substantial changes in methylation-expression correlation indicate that these genes are subject to epigenetic remodeling, where the differential activity of other factors break the expected relationship between both variables. Our findings suggest a complex regulatory landscape where a redistribution of local and large-scale chromatin repressive domains at differentially correlated genes (DCGs) creates epigenetic hotspots that modulate cancer-specific gene expression.

Sox9 mediates Notch1-induced mesenchymal features in lung adenocarcinoma

Sox9 has gained increasing importance both functionally and as a prognostic factor in cancer. We demonstrate a functional role for Sox9 in inducing a mesenchymal phenotype in lung ADC. We show that Sox9 mRNA and protein are overexpressed in lung ADC, particularly those with KRAS mutations. Sox9 expression correlated with the Notch target gene Hes1, and numerous other Notch pathway components. We observed that Sox9 is a potent inducer of lung cancer cell motility and invasion, and a negative regulator of E-cadherin, a key protein that is lost during epithelial-mesenchymal transition (EMT). Moreover, we show that Notch1 signaling directly regulates Sox9 expression through a SOX9 promoter binding site, independently of the TGF-β pathway, and that Sox9 participates in Notch-1 induced cell motility, cell invasion, and loss of E-cadherin expression. Together, the results identify a new functional role for a Notch1-Sox9 signaling axis in lung ADC that may explain the correlation of Sox9 with tumor progression, higher tumor grade, and poor lung cancer survival. In addition to Notch and TGF-β, Sox9 also acts downstream of NF-κB, BMP, EGFR, and Wnt/β-catenin signaling. Thus, Sox9 could potentially act as a hub to mediate cross-talk among key oncogenic pathways in lung ADC. Targeting Sox9 expression or transcriptional activity could potentially reduce resistance to targeted therapy for lung ADC caused by pathway redundancy.

F2RL3 methylation, lung cancer incidence and mortality

Smoking accounts for a large share of lung cancer. F2RL3 methylation was recently identified as a biomarker closely reflecting both current and past smoking exposure. We aimed to assess the associations of F2RL3 methylation with lung cancer incidence and mortality. In a large population-based cohort study, F2RL3 methylation was measured in baseline blood samples of 4,987 participants by MassARRAY. Associations of F2RL3 methylation and smoking with lung cancer incidence/mortality during a median follow-up of 10.9 years were assessed by Cox regression, controlling for potential confounders. The ability of F2RL3 methylation to predict lung cancer was examined by Harrell's C statistics. Hypomethylation at F2RL3 was strongly associated with both lung cancer incidence and mortality, with age- and sex-adjusted hazard ratios (HR; 95% CI) of 9.99 (5.61-17.79) and 16.86 (8.53-33.34), respectively, for participants whose methylation intensity were ≤0.54 compared with whose methylation intensity were ≥0.75. Strongly elevated HRs of 2.88 (1.42-5.84) and 5.17 (2.28-11.70) persisted even after controlling for multiple covariates including smoking status and pack-years. With fully adjusted HRs of 9.92 (2.88-34.12) and 16.48 (4.10-66.15), the associations between methylation and the two outcomes were particularly strong among participants≥65 years. Combination of F2RL3 methylation and pack-years predicted lung cancer incidence with high accuracy (optimism-corrected Harrell's C statistics = 0.86 for participants≥65 years). These findings suggested that F2RL3 methylation is a very strong predictor of lung cancer risk and mortality, particularly at older age. The potential implications of F2RL3 methylation for early detection, risk stratification and prevention of lung cancer warrant further exploration.

Identification and validation of gene module associated with lung cancer through coexpression network analysis

Lung cancer, a tumor with heterogeneous biology, is influenced by a complex network of gene interactions. Therefore, elucidating the relationships between genes and lung cancer is critical to attain further knowledge on tumor biology. In this study, we performed weighted gene coexpression network analysis to investigate the roles of gene networks in lung cancer regulation. Gene coexpression relationships were explored in 58 samples with tumorous and matched non-tumorous lungs, and six gene modules were identified on the basis of gene coexpression patterns. The overall expression of one module was significantly higher in the normal group than in the lung cancer group. This finding was validated across six datasets (all p values <0.01). The particular module was highly enriched for genes belonging to the biological Gene Ontology category "response to wounding" (adjusted p value = 4.28 × 10(-10)). A lung cancer-specific hub network (LCHN) consisting of 15 genes was also derived from this module. A support vector machine based on classification model robustly separated lung cancer from adjacent normal tissues in the validation datasets (accuracy ranged from 91.7% to 98.5%) by using the LCHN gene signatures as predictors. Eight genes in the LCHN are associated with lung cancer. Overall, we identified a gene module associated with lung cancer, as well as an LCHN consisting of hub genes that may be candidate biomarkers and therapeutic targets for lung cancer. This integrated analysis of lung cancer transcriptome provides an alternative strategy for identification of potential oncogenic drivers.

Reconfiguration of DNA methylation in aging

A complex interplay between multiple biological effects shapes the aging process. The advent of genome-wide quantitative approaches in the epigenetic field has highlighted the effective impact of epigenetic deregulation, particularly of DNA methylation, on aging. Age-associated alterations in DNA methylation are commonly grouped in the phenomenon known as "epigenetic drift" which is characterized by gradual extensive demethylation of genome and hypermethylation of a number of promoter-associated CpG islands. Surprisingly, specific DNA regions show directional epigenetic changes in aged individuals suggesting the importance of these events for the aging process. However, the epigenetic information obtained until now in aging needs a re-consideration due to the recent discovery of 5-hydroxymethylcytosine, a new DNA epigenetic mark present on genome. A recapitulation of the factors involved in the regulation of DNA methylation and the changes occurring in aging will be described in this review also considering the data available on 5 hmC.

In-depth proteomic analysis of six types of exudative pleural effusions for nonsmall cell lung cancer biomarker discovery

Pleural effusion (PE), a tumor-proximal body fluid, may be a promising source for biomarker discovery in human cancers. Because a variety of pathological conditions can lead to PE, characterization of the relative PE proteomic profiles from different types of PEs would accelerate discovery of potential PE biomarkers specifically used to diagnose pulmonary disorders. Using quantitative proteomic approaches, we identified 772 nonredundant proteins from six types of exudative PEs, including three malignant PEs (MPE, from lung, breast, and gastric cancers), one lung cancer paramalignant PE, and two benign diseases (tuberculosis and pneumonia). Spectral counting was utilized to semiquantify PE protein levels. Principal component analysis, hierarchical clustering, and Gene Ontology of cellular process analyses revealed differential levels and functional profiling of proteins in each type of PE. We identified 30 candidate proteins with twofold higher levels (q<0.05) in lung cancer MPEs than in the two benign PEs. Three potential markers, MET, DPP4, and PTPRF, were further verified by ELISA using 345 PE samples. The protein levels of these potential biomarkers were significantly higher in lung cancer MPE than in benign diseases or lung cancer paramalignant PE. The area under the receiver-operator characteristic curve for three combined biomarkers in discriminating lung cancer MPE from benign diseases was 0.903. We also observed that the PE protein levels were more clearly discriminated in effusions in which the cytological examination was positive and that they would be useful in rescuing the false negative of cytological examination in diagnosis of nonsmall cell lung cancer-MPE. Western blotting analysis further demonstrated that MET overexpression in lung cancer cells would contribute to the elevation of soluble MET in MPE. Our results collectively demonstrate the utility of label-free quantitative proteomic approaches in establishing differential PE proteomes and provide a new database of proteins that can be used to facilitate identification of pulmonary disorder-related biomarkers.

LKB1 Loss induces characteristic patterns of gene expression in human tumors associated with NRF2 activation and attenuation of PI3K-AKT

Introduction:

Inactivation of serine/threonine kinase 11 (STK11 or LKB1) is common in lung cancer, and understanding the pathways and phenotypes altered as a consequence will aid the development of targeted therapeutic strategies. Gene and protein expressions in a murine model of v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (Kras)-mutant lung cancer have been studied to gain insight into the biology of these tumors. However, the molecular consequences of LKB1 loss in human lung cancer have not been fully characterized.

Methods:

We studied gene expression profiles associated with LKB1 loss in resected lung adenocarcinomas, non–small-cell lung cancer cell lines, and murine tumors. The biological significance of dysregulated genes was interpreted using gene set enrichment and transcription factor analyses and also by integration with somatic mutations and proteomic data.

Results:

Loss of LKB1 is associated with consistent gene expression changes in resected human lung cancers and cell lines that differ substantially from the mouse model. Our analysis implicates novel biological features associated with LKB1 loss, including altered mitochondrial metabolism, activation of the nuclear respiratory factor 2 (NRF2) transcription factor by kelch-like ECH-associated protein 1 (KEAP1) mutations, and attenuation of the phosphatidylinositiol 3-kinase and v-akt murine thymoma viral oncogene homolog (PI3K/AKT) pathway. Furthermore, we derived a 16-gene classifier that accurately predicts LKB1 mutations and loss by nonmutational mechanisms. In vitro, transduction of LKB1 into LKB1-mutant cell lines results in attenuation of this signature.

Conclusion:

Loss of LKB1 defines a subset of lung adenocarcinomas associated with characteristic molecular phenotypes and distinctive gene expression features. Studying these effects may improve our understanding of the biology of these tumors and lead to the identification of targeted treatment strategies.

DAL-1 attenuates epithelial-to mesenchymal transition in lung cancer

BACKGROUND

Epithelial-to mesenchymal transition (EMT) involves in metastasis, causing loss of epithelial polarity. Metastasis is the major cause of carcinoma-induced death, but mechanisms are poorly understood. Here we identify differentially expressed in adenocarcinoma of the lung-1 (DAL-1), a protein belongs to the membrane-associated cytoskeleton protein 4.1 family, as an efficient suppressor of EMT in lung cancer.

METHODS

The relationship between DAL-1 and EMT markers were analyzed by using immunohistochemistry in the clinical lung cancer tissues. Quantitative real-time PCR and western blot were used to characterize the expression of the EMT indicator mRNAs and proteins in DAL-1 overexpressed or knockdown cells. DAL-1 combined proteins were assessed by co-immunoprecipitation.

RESULTS

DAL-1 levels were strongly reduced even lost in lymph node metastasis and advanced pathological stage of human lung carcinomas. Overexpression of DAL-1 altered the expression of numerous EMT markers, such as E-cadherin, β-catenin Vimentin and N-cadherin expression, meanwhile changed the morphological shape of lung cancer cells, and whereas silencing DAL-1 had an opposite effect. DAL-1 directly combined with E-cadherin promoter and regulated its expression that could be the reason for impairing EMT and decreasing cell migration and invasion. Strikingly, HSPA5 was found as DAL-1 direct binding protein.

CONCLUSIONS

These results suggest that tumor suppressor DAL-1 could also attenuate EMT and be important for tumor metastasis in the early transformation process in lung cancer.

Integrative analysis of DNA methylation and gene expression data identifies EPAS1 as a key regulator of COPD

Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a ‘causal’ role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology.

Chronic Obstructive Pulmonary Disease (COPD) is a common lung disease. It is the fourth leading cause of death in the world and is expected to be the third by 2020. COPD is a heterogeneous and complex disease consisting of obstruction in the small airways, emphysema, and chronic bronchitis. COPD is generally caused by exposure to noxious particles or gases, most commonly from cigarette smoking. However, only 20–25% of smokers develop clinically significant airflow obstruction. Smoking is known to cause epigenetic changes in lung tissues. Thus, genetics, epigenetic, and their interaction with environmental factors play an important role in COPD pathogenesis and progression. Currently, there are no therapeutics that can reverse COPD progression. In order to identify new targets that may lead to the development of therapeutics for curing COPD, we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity.

DNA methylation and RNA expression profiles in lung adenocarcinomas of never-smokers

Lung cancer occurs in never-smokers. Epigenetic changes in lung cancer potentially represent important diagnostic, prognostic, and therapeutic targets. We compared DNA methylation profiles of 28 adenocarcinomas of the lungs of never-smokers with paired adjacent nonmalignant lung tissue. We correlated differential methylation changes with gene expression changes from the same 28 sample pairs. Using principal component analysis, we observed a distinct separation in methylation profiles between tumor and adjacent nonmalignant lung tissue. Tumors were generally hypomethylated compared with adjacent nonmalignant tissue. Of 1,906 CpG sites differentially methylated between tumor and nonmalignant tissue, 1,198 were within classically defined CpG islands where tumors were hypermethylated compared with nonmalignant tissue. A total of 708 sites were outside CpG islands where tumors were hypomethylated compared with nonmalignant tissue. There were significant differences in expression of 351 genes (23%) of the 1,522 genes matched to the differentially methylated CpG sites. Genes that were not significantly differentially expressed and were hypermethylated within CpG sites were enriched for homeobox genes. These results suggest that the methylation profiles of lung adenocarcinomas of never-smokers and adjacent nonmalignant lung tissue are significantly different. Despite the differential methylation of homeobox genes, no significant changes in expression of these genes were detected.

An Arf-Egr-C/EBPβ pathway linked to ras-induced senescence and cancer

Oncogene-induced senescence (OIS) protects normal cells from transformation by Ras, whereas cells lacking p14/p19(Arf) or other tumor suppressors can be transformed. The transcription factor C/EBPβ is required for OIS in primary fibroblasts but is downregulated by H-Ras(V12) in immortalized NIH 3T3 cells through a mechanism involving p19(Arf) loss. Here, we report that members of the serum-induced early growth response (Egr) protein family are also downregulated in 3T3(Ras) cells and directly and redundantly control Cebpb gene transcription. Egr1, Egr2, and Egr3 recognize three sites in the Cebpb promoter and associate transiently with this region after serum stimulation, coincident with Cebpb induction. Codepletion of all three Egrs prevented Cebpb expression, and serum induction of Egrs was significantly blunted in 3T3(Ras) cells. Egr2 and Egr3 levels were also reduced in Ras(V12)-expressing p19(Arf) null mouse embryonic fibroblasts (MEFs), and overall Egr DNA-binding activity was suppressed in Arf-deficient but not wild-type (WT) MEFs, leading to Cebpb downregulation. Analysis of human cancers revealed a strong correlation between EGR levels and CEBPB expression, regardless of whether CEBPB was increased or decreased in tumors. Moreover, overexpression of Egrs in tumor cell lines induced CEBPB and inhibited proliferation. Thus, our findings identify the Arf-Egr-C/EBPβ axis as an important determinant of cellular responses (senescence or transformation) to oncogenic Ras signaling.

Heterogeneous DNA methylation contributes to tumorigenesis through inducing the loss of coexpression connectivity in colorectal cancer

Increasing evidence indicates the high heterogeneity of cancer cells. Recent studies have revealed distinct subtypes of DNA methylation in colorectal cancer (CRC); however, the mechanism of heterogeneous methylation remains poorly understood. Gene expression is a natural, intermediate quantitative trait that bridges genotypic and phenotypic features. In this work, we studied the role of heterogeneous DNA methylation in tumorigenesis via gene expression analyses. Specifically, we integrated methylation and expression data in normal and tumor tissues, and examined the perturbations in coexpression patterns. We found that the heterogeneity of methylation leads to significant loss of coexpression connectivity in CRC; this finding was validated in an independent cohort. Functional analyses showed that the lost coexpression partners participate in important cancer-related pathways/networks, such as ErbB and mitogen-activated protein kinase (MAPK) signaling pathways. Our analyses suggest that the loss of coexpression connectivity induced by methylation heterogeneity might play an important role in CRC. To our knowledge, this is the first study to interpret methylation heterogeneity in cancer from the perspective of coexpression perturbation. Our results provide new perspectives in tumor biology and may facilitate the identification of potential biomedical therapies for cancer treatment.

Propensity score method for partially matched omics studies

This paper focuses on the problem of partially matched samples in the presence of confounders. We propose using propensity score matching to adjust for confounding factors for the subset of data with incomplete pairs, followed by integrating the P-values computed from the complete and incomplete paired samples, respectively. Several simulations and a case study on DNA methylation are considered to evaluate the operating characteristics of the proposed method.

Smoking status impacts microRNA mediated prognosis and lung adenocarcinoma biology

Background

Cigarette smoke is associated with the majority of lung cancers: however, 25% of lung cancer patients are non-smokers, and half of all newly diagnosed lung cancer patients are former smokers. Lung tumors exhibit distinct epidemiological, clinical, pathological, and molecular features depending on smoking status, suggesting divergent mechanisms underlie tumorigenesis in smokers and non-smokers. MicroRNAs (miRNAs) are integral contributors to tumorigenesis and mediate biological responses to smoking. Based on the hypothesis that smoking-specific miRNA differences in lung adenocarcinomas reflect distinct tumorigenic processes selected by different smoking and non-smoking environments, we investigated the contribution of miRNA disruption to lung tumor biology and patient outcome in the context of smoking status.

Methods

We applied a whole transcriptome sequencing based approach to interrogate miRNA levels in 94 patient-matched lung adenocarcinoma and non-malignant lung parenchymal tissue pairs from current, former and never smokers.

Results

We discovered novel and distinct smoking status-specific patterns of miRNA and miRNA-mediated gene networks, and identified miRNAs that were prognostically significant in a smoking dependent manner.

Conclusions

We conclude that miRNAs disrupted in a smoking status-dependent manner affect distinct cellular pathways and differentially influence lung cancer patient prognosis in current, former and never smokers. Our findings may represent promising biologically relevant markers for lung cancer prognosis or therapeutic intervention.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2407-14-778) contains supplementary material, which is available to authorized users.

jNMFMA: a joint non-negative matrix factorization meta-analysis of transcriptomics data

MOTIVATION

Tremendous amount of omics data being accumulated poses a pressing challenge of meta-analyzing the heterogeneous data for mining new biological knowledge. Most existing methods deal with each gene independently, thus often resulting in high false positive rates in detecting differentially expressed genes (DEG). To our knowledge, no or little effort has been devoted to methods that consider dependence structures underlying transcriptomics data for DEG identification in meta-analysis context.

RESULTS

This article proposes a new meta-analysis method for identification of DEGs based on joint non-negative matrix factorization (jNMFMA). We mathematically extend non-negative matrix factorization (NMF) to a joint version (jNMF), which is used to simultaneously decompose multiple transcriptomics data matrices into one common submatrix plus multiple individual submatrices. By the jNMF, the dependence structures underlying transcriptomics data can be interrogated and utilized, while the high-dimensional transcriptomics data are mapped into a low-dimensional space spanned by metagenes that represent hidden biological signals. jNMFMA finally identifies DEGs as genes that are associated with differentially expressed metagenes. The ability of extracting dependence structures makes jNMFMA more efficient and robust to identify DEGs in meta-analysis context. Furthermore, jNMFMA is also flexible to identify DEGs that are consistent among various types of omics data, e.g. gene expression and DNA methylation. Experimental results on both simulation data and real-world cancer data demonstrate the effectiveness of jNMFMA and its superior performance over other popular approaches.

AVAILABILITY AND IMPLEMENTATION

R code for jNMFMA is available for non-commercial use via http://micblab.iim.ac.cn/Download/.

CONTACT

hqwang@ustc.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genome-wide DNA methylation analysis of lung carcinoma reveals one neuroendocrine and four adenocarcinoma epitypes associated with patient outcome

PURPOSE

Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. However, whether clinically relevant subgroups based on DNA methylation patterns exist in lung cancer remains unclear.

EXPERIMENTAL DESIGN

Whole-genome DNA methylation analysis using 450K Illumina BeadArrays was performed on 12 normal lung tissues and 124 tumors, including 83 adenocarcinomas, 23 squamous cell carcinomas (SqCC), 1 adenosquamous cancer, 5 large cell carcinomas, 9 large cell neuroendocrine carcinomas (LCNEC), and 3 small-cell carcinomas (SCLC). Unsupervised bootstrap clustering was performed to identify DNA methylation subgroups, which were validated in 695 adenocarcinomas and 122 SqCCs. Subgroups were characterized by clinicopathologic factors, whole-exome sequencing data, and gene expression profiles.

RESULTS

Unsupervised analysis identified five DNA methylation subgroups (epitypes). One epitype was distinctly associated with neuroendocrine tumors (LCNEC and SCLC). For adenocarcinoma, remaining four epitypes were associated with unsupervised and supervised gene expression phenotypes, and differences in molecular features, including global hypomethylation, promoter hypermethylation, genomic instability, expression of proliferation-associated genes, and mutations in KRAS, TP53, KEAP1, SMARCA4, and STK11. Furthermore, these epitypes were associated with clinicopathologic features such as smoking history and patient outcome.

CONCLUSIONS

Our findings highlight one neuroendocrine and four adenocarcinoma epitypes associated with molecular and clinicopathologic characteristics, including patient outcome. This study demonstrates the possibility to further subgroup lung cancer, and more specifically adenocarcinomas, based on epigenetic/molecular classification that could lead to more accurate tumor classification, prognostication, and tailored patient therapy.

The splicing factor RBM4 controls apoptosis, proliferation, and migration to suppress tumor progression

Splicing dysregulation is one of the molecular hallmarks of cancer. However, the underlying molecular mechanisms remain poorly defined. Here we report that the splicing factor RBM4 suppresses proliferation and migration of various cancer cells by specifically controlling cancer-related splicing. Particularly, RBM4 regulates Bcl-x splicing to induce apoptosis, and coexpression of Bcl-xL partially reverses the RBM4-mediated tumor suppression. Moreover, RBM4 antagonizes an oncogenic splicing factor, SRSF1, to inhibit mTOR activation. Strikingly, RBM4 expression is decreased dramatically in cancer patients, and the RBM4 level correlates positively with improved survival. In addition to providing mechanistic insights of cancer-related splicing dysregulation, this study establishes RBM4 as a tumor suppressor with therapeutic potential and clinical values as a prognostic factor.

Lung cancer transcriptomes refined with laser capture microdissection

We evaluated the importance of tumor cell selection for generating gene signatures in non-small cell lung cancer. Tumor and nontumor tissue from macroscopically dissected (Macro) surgical specimens (31 pairs from 32 subjects) was homogenized, extracted, amplified, and hybridized to microarrays. Adjacent scout sections were histologically mapped; sets of approximately 1000 tumor cells and nontumor cells (alveolar or bronchial) were procured by laser capture microdissection (LCM). Within histological strata, LCM and Macro specimens exhibited approximately 67% to 80% nonoverlap in differentially expressed (DE) genes. In a representative subset, LCM uniquely identified 300 DE genes in tumor versus nontumor specimens, largely attributable to cell selection; 382 DE genes were common to Macro, Macro with preamplification, and LCM platforms. RT-qPCR validation in a 33-gene subset was confirmatory (ρ = 0.789 to 0.964, P = 0.0013 to 0.0028). Pathway analysis of LCM data suggested alterations in known cancer pathways (cell growth, death, movement, cycle, and signaling components), among others (eg, immune, inflammatory). A unique nine-gene LCM signature had higher tumor-nontumor discriminatory accuracy (100%) than the corresponding Macro signature (87%). Comparison with Cancer Genome Atlas data sets (based on homogenized Macro tissue) revealed both substantial overlap and important differences from LCM specimen results. Thus, cell selection via LCM enhances expression profiling precision, and confirms both known and under-appreciated lung cancer genes and pathways.

MODMatcher: multi-omics data matcher for integrative genomic analysis

Errors in sample annotation or labeling often occur in large-scale genetic or genomic studies and are difficult to avoid completely during data generation and management. For integrative genomic studies, it is critical to identify and correct these errors. Different types of genetic and genomic data are inter-connected by cis-regulations. On that basis, we developed a computational approach, Multi-Omics Data Matcher (MODMatcher), to identify and correct sample labeling errors in multiple types of molecular data, which can be used in further integrative analysis. Our results indicate that inspection of sample annotation and labeling error is an indispensable data quality assurance step. Applied to a large lung genomic study, MODMatcher increased statistically significant genetic associations and genomic correlations by more than two-fold. In a simulation study, MODMatcher provided more robust results by using three types of omics data than two types of omics data. We further demonstrate that MODMatcher can be broadly applied to large genomic data sets containing multiple types of omics data, such as The Cancer Genome Atlas (TCGA) data sets.

Many human diseases are complex with multiple genetic and environmental causal factors interacting together to give rise to disease phenotypes. Such factors affect biological systems through many layers of regulations, including transcriptional and epigenetic regulation, and protein changes. To fully understand their molecular mechanisms, complex diseases are often studied in diverse dimensions including genetics (genotype variations by single nucleotide polymorphism (SNP) arrays or whole exome sequencing), transcriptomics, epigenetics, and proteomics. However, errors in sample annotation or labeling often occur in large-scale genetic and genomic studies and are difficult to avoid completely during data generation and management. Identifying and correcting these errors are critical for integrative genomic studies. In this study, we developed a computational approach, Multi-Omics Data Matcher (MODMatcher), to identify and correct sample labeling errors based on multiple types of molecular data before further integrative analysis. Our results indicate that signals increased more than 100% after correction of sample labeling errors in a large lung genomic study. Our method can be broadly applied to large genomic data sets with multiple types of omics data, such as TCGA (The Cancer Genome Atlas) data sets.

Unmethylation of the CHRNB4 gene is an unfavorable prognostic factor in non-small cell lung cancer

OBJECTIVES

Lung cancer is the leading cause of cancer-related deaths and is currently a major health problem owing to difficulties in diagnosis at the early stage of the disease. Changes in DNA methylation status have now been identified as a critical component in the initiation of lung cancer, and the detection of DNA methylation is expected to be an important method for the early diagnosis of lung cancer. Nicotine, the principal tobacco alkaloid, directly contributes to lung carcinogenesis through the activation of nicotinic acetylcholine receptors (nAchRs).

MATERIALS AND METHODS

To investigate the role of the CHRNB4 gene, which encodes the nAchR β4 subunit that is ubiquitously expressed on lung epithelial cells, we analyzed its methylation status in 266 patients with non-small cell lung cancer (NSCLC) by using methylation-specific polymerase chain reaction and compared it with clinicopathological parameters.

RESULTS AND CONCLUSION

The frequency of CHRNB4 unmethylation was 13.5% and 8.3% in malignant and nonmalignant tissues, respectively. CHRNB4 demethylation was associated with upregulation of its mRNA expression and was more frequent in squamous cell carcinoma and pathological stages II-IIIA disease than in adenocarcinoma and pathological stage I disease, respectively (P=0.003 and P=0.01, respectively). Univariate and multivariate analyses showed that CHRNB4 unmethylation was significantly associated with unfavorable overall survival in the entire patient group as well as in men and ever-smokers. These results suggest that epigenetic regulation of CHRNB4 may affect tumor progression and survival in patients with NSCLC. Further investigation into the molecular basis of the role of CHRNB4 in the progression of NSCLC is warranted.

The potential role of extracellular regulatory kinase in the survival of patients with early stage adenocarcinoma

BACKGROUND

Lung cancer is among the most common types of neoplasias, and adenocarcinoma is the most frequent histological type. There is currently an extensive search for prognostic biomarkers of nonsmall cell lung cancer (NSCLC).

METHODS

We analyzed the correlation of clinical data and patient survival with the levels of activated extracellular regulatory kinase (ERK) in histological samples of surgically resected early stage lung adenocarcinoma. We randomly selected 36 patients with stage I or II lung adenocarcinoma who underwent pulmonary lobectomy between 1998 and 2004. Patients were divided into the following two groups according to immunohistochemical profile: a group with <15% ERK-positive tumor cells and a group with ≥15% ERK-positive tumor cells. For data comparison, an enrichment analysis of a microarray database was performed (GSE29016, n=72).

RESULTS

Activated ERK levels were ≥15% and <15% in 21 (58%) and 15 (42%) patients, respectively. There were no statistically significant differences in age, sex, smoking history, and body mass index (BMI) among the groups stratified by ERK levels. The survival rate was lower in the ERK ≥15% group than in the ERK <15% group (P=0.045). Enrichment analyses showed no correlation between variations in gene expression of ERK in patients with adenocarcinoma and survival rates in patients with stage I and combined stage II + III disease.

CONCLUSIONS

Our findings suggest that high ERK positivity in cells from biological samples of lung adenocarcinoma is related with tumor aggressiveness and a poorer prognosis.

Methylation profiles reveal distinct subgroup of hepatocellular carcinoma patients with poor prognosis

Hepatocellular Carcinoma (HCC) is one of the leading causes of cancer-associated mortality worldwide. However, the role of epigenetic changes such as aberrant DNA methylation in hepatocarcinogenesis remains largely unclear. In this study, we examined the methylation profiles of 59 HCC patients. Using consensus hierarchical clustering with feature selection, we identified three tumor subgroups based on their methylation profiles and correlated these subgroups with clinicopathological parameters. Interestingly, one tumor subgroup is different from the other 2 subgroups and the methylation profile of this subgroup is the most distinctly different from the non-tumorous liver tissues. Significantly, this subgroup of patients was found to be associated with poor overall as well as disease-free survival. To further understand the pathways modulated by the deregulation of methylation in HCC patients, we integrated data from both the methylation as well as the gene expression profiles of these 59 HCC patients. In these patients, while 4416 CpG sites were differentially methylated between the tumors compared to the adjacent non-tumorous tissues, only 536 of these CpG sites were associated with differences in the expression of their associated genes. Pathway analysis revealed that forty-four percent of the most significant upstream regulators of these 536 genes were involved in inflammation-related NFκB pathway. These data suggest that inflammation via the NFκB pathway play an important role in modulating gene expression of HCC patients through methylation. Overall, our analysis provides an understanding on aberrant methylation profile in HCC patients.

Galectin-4 expression is associated with reduced lymph node metastasis and modulation of Wnt/β-catenin signalling in pancreatic adenocarcinoma

Galectin-4 (Gal-4) has been recently identified as a pivotal factor in the migratory capabilities of a set of defined pancreatic ductal adenocarcinoma (PDAC) cell lines using zebrafish as a model system. Here we evaluated the expression of Gal-4 in PDAC tissues selected according to their lymph node metastatic status (N0 vs. N1), and investigated the therapeutic potential of targeting the cross-link with the Wnt signaling pathway in primary PDAC cells. Analysis of Gal-4 expression in PDACs showed high expression of Gal-4 in 80% of patients without lymph node metastasis, whereas 70% of patients with lymph node metastases had low Gal-4 expression. Accordingly, in primary PDAC cells high Gal-4 expression was negatively associated with migratory and invasive ability in vitro and in vivo. Knockdown of Gal-4 in primary PDAC cells with high Gal-4 expression resulted in significant increase of invasion (40%) and migration (50%, P<0.05), whereas enforced expression of Gal-4 in primary cells with low Gal-4 expression reduced the migratory and invasive behavior compared to the control cells. Gal-4 markedly reduces β-catenin levels in the cell, counteracting the function of Wnt signaling, as was assessed by down-regulation of survivin and cyclin D1. Furthermore, Gal-4 sensitizes PDAC cells to the Wnt inhibitor ICG-001, which interferes with the interaction between CREB binding protein (CBP) and β-catenin. Collectively, our data suggest that Gal-4 lowers the levels of cytoplasmic β-catenin, which may lead to lowered availability of nuclear β-catenin, and consequently diminished levels of nuclear CBP-β-catenin complex and reduced activation of the Wnt target genes. Our findings provide novel insights into the role of Gal-4 in PDAC migration and invasion, and support the analysis of Gal-4 for rational targeting of Wnt/β-catenin signaling in the treatment of PDAC.

A search for novel cancer/testis antigens in lung cancer identifies VCX/Y genes, expanding the repertoire of potential immunotherapeutic targets

Cancer/testis (CT) antigens are potential immunotherapeutic targets in cancer. However, the expression of particular antigens is limited to a subset of tumors of a given type. Thus, there is a need to identify antigens with complementary expression patterns for effective therapeutic intervention. In this study, we searched for genes that were distinctly expressed at a higher level in lung tumor tissue and the testes compared with other nontumor tissues and identified members of the VCX/Y gene family as novel CT antigens. VCX3A, a member of the VCX/Y gene family, was expressed at the protein level in approximately 20% of lung adenocarcinomas and 35% of squamous cell carcinomas, but not expressed in normal lung tissues. Among CT antigens with concordant mRNA and protein expression levels, four CT antigens, XAGE1, VCX, IL13RA2, and SYCE1, were expressed, alone or in combination, in about 80% of lung adenocarcinoma tumors. The CT antigen VCX/Y gene family broadens the spectrum of CT antigens expressed in lung adenocarcinomas for clinical applications.

Epigenetic clustering of lung adenocarcinomas based on DNA methylation profiles in adjacent lung tissue: Its correlation with smoking history and chronic obstructive pulmonary disease

The aim of this study was to clarify the significance of DNA methylation alterations during lung carcinogenesis. Infinium assay was performed using 139 paired samples of non-cancerous lung tissue (N) and tumorous tissue (T) from a learning cohort of patients with lung adenocarcinomas (LADCs). Fifty paired N and T samples from a validation cohort were also analyzed. DNA methylation alterations on 1,928 probes occurred in N samples relative to normal lung tissue from patients without primary lung tumors, and were inherited by, or strengthened in, T samples. Unsupervised hierarchical clustering using DNA methylation levels in N samples on all 26,447 probes subclustered patients into Cluster I (n = 32), Cluster II (n = 35) and Cluster III (n = 72). LADCs in Cluster I developed from the inflammatory background in chronic obstructive pulmonary disease (COPD) in heavy smokers and were locally invasive. Most patients in Cluster II were non-smokers and had a favorable outcome. LADCs in Cluster III developed in light smokers were most aggressive (frequently showing lymphatic and blood vessel invasion, lymph node metastasis and an advanced pathological stage), and had a poor outcome. DNA methylation levels of hallmark genes for each cluster, such as IRX2, HOXD8, SPARCL1, RGS5 and EI24, were again correlated with clinicopathological characteristics in the validation cohort. DNA methylation profiles reflecting carcinogenetic factors such as smoking and COPD appear to be established in non-cancerous lung tissue from patients with LADCs and may determine the aggressiveness of tumors developing in individual patients, and thus patient outcome.

Development of a multiplex methylation specific PCR suitable for (early) detection of non-small cell lung cancer

Lung cancer is a worldwide health problem and a leading cause of cancer-related deaths. Silencing of potential tumor suppressor genes (TSGs) by aberrant promoter methylation is an early event in the initiation and development of cancer. Thus, methylated cancer type-specific TSGs in DNA can serve as useful biomarkers for early cancer detection. We have now developed a "Multiplex Methylation Specific PCR" (MMSP) assay for analysis of the methylation status of multiple potential TSGs by a single PCR reaction. This method will be useful for early diagnosis and treatment outcome studies of non-small cell lung cancer (NSCLC). Genome-wide CpG methylation and expression microarrays were performed on lung cancer tissues and matched distant non-cancerous tissues from three NSCLC patients from China. Thirty-eight potential TSGs were selected and analyzed by methylation PCR on bisulfite treated DNA. On the basis of sensitivity and specificity, six marker genes, HOXA9, TBX5, PITX2, CALCA, RASSF1A, and DLEC1, were selected to establish the MMSP assay. This assay was then used to analyze lung cancer tissues and matched distant non-cancerous tissues from 70 patients with NSCLC, as well as 24 patients with benign pulmonary lesion as controls. The sensitivity of the assay was 99% (69/70). HOXA9 and TBX5 were the 2 most sensitive marker genes: 87% (61/70) and 84% (59/70), respectively. RASSF1A and DLEC1 showed the highest specificity at 99% (69/70). Using the criterion of identifying at least any two methylated marker genes, 61/70 cancer samples were positive, corresponding to a sensitivity of 87% and a specificity of 94%. Early stage I or II NSCLC could even be detected with a 100% specificity and 86% sensitivity. In conclusion, MMSP has the potential to be developed into a population-based screening tool and can be useful for early diagnosis of NSCLC. It might also be suitable for monitoring treatment outcome and recurrence.

Hypermethylation in the ZBTB20 gene is associated with major depressive disorder

BACKGROUND

Although genetic variation is believed to contribute to an individual's susceptibility to major depressive disorder, genome-wide association studies have not yet identified associations that could explain the full etiology of the disease. Epigenetics is increasingly believed to play a major role in the development of common clinical phenotypes, including major depressive disorder.

RESULTS

Genome-wide MeDIP-Sequencing was carried out on a total of 50 monozygotic twin pairs from the UK and Australia that are discordant for depression. We show that major depressive disorder is associated with significant hypermethylation within the coding region of ZBTB20, and is replicated in an independent cohort of 356 unrelated case-control individuals. The twins with major depressive disorder also show increased global variation in methylation in comparison with their unaffected co-twins. ZBTB20 plays an essential role in the specification of the Cornu Ammonis-1 field identity in the developing hippocampus, a region previously implicated in the development of major depressive disorder.

CONCLUSIONS

Our results suggest that aberrant methylation profiles affecting the hippocampus are associated with major depressive disorder and show the potential of the epigenetic twin model in neuro-psychiatric disease.

Discovery and development of DNA methylation-based biomarkers for lung cancer

Lung cancer remains the primary cause of cancer-related deaths worldwide. Improved tools for early detection and therapeutic stratification would be expected to increase the survival rate for this disease. Alterations in the molecular pathways that drive lung cancer, which include epigenetic modifications, may provide biomarkers to help address this major unmet clinical need. Epigenetic changes, which are defined as heritable changes in gene expression that do not alter the primary DNA sequence, are one of the hallmarks of cancer, and prevalent in all types of cancer. These modifications represent a rich source of biomarkers that have the potential to be implemented in clinical practice. This perspective describes recent advances in the discovery of epigenetic biomarkers in lung cancer, specifically those that result in the methylation of DNA at CpG sites. We discuss one approach for methylation-based biomarker assay development that describes the discovery at a genome-scale level, which addresses some of the practical considerations for design of assays that can be implemented in the clinic. We emphasize that an integrated technological approach will enable the development of clinically useful DNA methylation-based biomarker assays. While this article focuses on current literature and primary research findings in lung cancer, the principles we describe here apply to the discovery and development of epigenetic biomarkers for other types of cancer.

Accounting for population stratification in DNA methylation studies

DNA methylation is an important epigenetic mechanism that has been linked to complex diseases and is of great interest to researchers as a potential link between genome, environment, and disease. As the scale of DNA methylation association studies approaches that of genome-wide association studies, issues such as population stratification will need to be addressed. It is well-documented that failure to adjust for population stratification can lead to false positives in genetic association studies, but population stratification is often unaccounted for in DNA methylation studies. Here, we propose several approaches to correct for population stratification using principal components (PCs) from different subsets of genome-wide methylation data. We first illustrate the potential for confounding due to population stratification by demonstrating widespread associations between DNA methylation and race in 388 individuals (365 African American and 23 Caucasian). We subsequently evaluate the performance of our PC-based approaches and other methods in adjusting for confounding due to population stratification. Our simulations show that (1) all of the methods considered are effective at removing inflation due to population stratification, and (2) maximum power can be obtained with single-nucleotide polymorphism (SNP)-based PCs, followed by methylation-based PCs, which outperform both surrogate variable analysis and genomic control. Among our different approaches to computing methylation-based PCs, we find that PCs based on CpG sites chosen for their potential to proxy nearby SNPs can provide a powerful and computationally efficient approach to adjust for population stratification in DNA methylation studies when genome-wide SNP data are unavailable.

Ectopic activation of germline and placental genes identifies aggressive metastasis-prone lung cancers

Activation of normally silent tissue-specific genes and the resulting cell "identity crisis" are the unexplored consequences of malignant epigenetic reprogramming. We designed a strategy for investigating this reprogramming, which consisted of identifying a large number of tissue-restricted genes that are epigenetically silenced in normal somatic cells and then detecting their expression in cancer. This approach led to the demonstration that large-scale "off-context" gene activations systematically occur in a variety of cancer types. In our series of 293 lung tumors, we identified an ectopic gene expression signature associated with a subset of highly aggressive tumors, which predicted poor prognosis independently of the TNM (tumor size, node positivity, and metastasis) stage or histological subtype. The ability to isolate these tumors allowed us to reveal their common molecular features characterized by the acquisition of embryonic stem cell/germ cell gene expression profiles and the down-regulation of immune response genes. The methodical recognition of ectopic gene activations in cancer cells could serve as a basis for gene signature-guided tumor stratification, as well as for the discovery of oncogenic mechanisms, and expand the understanding of the biology of very aggressive tumors.

DNA methylation profiling of well-differentiated thyroid cancer uncovers markers of recurrence free survival

Thyroid cancer is a heterogeneous disease with several subtypes characterized by cytological, histological and genetic alterations, but the involvement of epigenetics is not well understood. Here, we investigated the role of aberrant DNA methylation in the development of well-differentiated thyroid tumors. We performed genome-wide DNA methylation profiling in the largest well-differentiated thyroid tumor series reported to date, comprising 83 primary tumors as well as 8 samples of adjacent normal tissue. The epigenetic profiles were closely related to not only tumor histology but also the underlying driver mutation; we found that follicular tumors had higher levels of methylation, which seemed to accumulate in a progressive manner along the tumorigenic process from adenomas to carcinomas. Furthermore, tumors harboring a BRAF or RAS mutation had a larger number of hypo- or hypermethylation events, respectively. The aberrant methylation of several candidate genes potentially related to thyroid carcinogenesis was validated in an independent series of 52 samples. Furthermore, through the integration of methylation and transcriptional expression data, we identified genes whose expression is associated with the methylation status of their promoters. Finally, by integrating clinical follow-up information with methylation levels we propose etoposide-induced 2.4 and Wilms tumor 1 as novel prognostic markers related to recurrence-free survival. This comprehensive study provides insights into the role of DNA methylation in well-differentiated thyroid cancer development and identifies novel markers associated with recurrence-free survival.

Immortality, but not oncogenic transformation, of primary human cells leads to epigenetic reprogramming of DNA methylation and gene expression

Tumourigenic transformation of normal cells into cancer typically involves several steps resulting in acquisition of unlimited growth potential, evasion of apoptosis and non-responsiveness to growth inhibitory signals. Both genetic and epigenetic changes can contribute to cancer development and progression. Given the vast genetic heterogeneity of human cancers and difficulty to monitor cancer-initiating events in vivo, the precise relationship between acquisition of genetic mutations and the temporal progression of epigenetic alterations in transformed cells is largely unclear. Here, we use an in vitro model system to investigate the contribution of cellular immortality and oncogenic transformation of primary human cells to epigenetic reprogramming of DNA methylation and gene expression. Our data demonstrate that extension of replicative life span of the cells is sufficient to induce accumulation of DNA methylation at gene promoters and large-scale changes in gene expression in a time-dependent manner. In contrast, continuous expression of cooperating oncogenes in immortalized cells, although essential for anchorage-independent growth and evasion of apoptosis, does not affect de novo DNA methylation at promoters and induces subtle expression changes. Taken together, these observations imply that cellular immortality promotes epigenetic adaptation to highly proliferative state, whereas transforming oncogenes confer additional properties to transformed human cells.

The chromatin remodeller CHD8 is required for E2F-dependent transcription activation of S-phase genes

The precise regulation of S-phase-specific genes is critical for cell proliferation. How the repressive chromatin configuration mediated by the retinoblastoma protein and repressor E2F factors changes at the G1/S transition to allow transcription activation is unclear. Here we show ChIP-on-chip studies that reveal that the chromatin remodeller CHD8 binds ∼ 2000 transcriptionally active promoters. The spectrum of CHD8 target genes was enriched in E2F-dependent genes. We found that CHD8 binds E2F-dependent promoters at the G1/S transition but not in quiescent cells. Consistently, CHD8 was required for G1/S-specific expression of these genes and for cell cycle re-entry on serum stimulation of quiescent cells. We also show that CHD8 interacts with E2F1 and, importantly, loading of E2F1 and E2F3, but not E2F4, onto S-specific promoters, requires CHD8. However, CHD8 recruiting is independent of these factors. Recruiting of MLL histone methyltransferase complexes to S-specific promoters was also severely impaired in the absence of CHD8. Furthermore, depletion of CHD8 abolished E2F1 overexpression-dependent S-phase stimulation of serum-starved cells, highlighting the essential role of CHD8 in E2F-dependent transcription activation.

DNA methylation data analysis and its application to cancer research

With the rapid development of genome-wide high-throughput technologies, including expression arrays, SNP arrays and next-generation sequencing platforms, enormous amounts of molecular data have been generated and deposited in the public domain. The application of computational approaches is required to yield biological insights from this enormous, ever-growing resource. A particularly interesting subset of these resources is related to epigenetic regulation, with DNA methylation being the most abundant data type. In this paper, we will focus on the analysis of DNA methylation data and its application to cancer studies. We first briefly review the molecular techniques that generate such data, much of which has been obtained with the use of the most recent version of Infinium HumanMethylation450 BeadChip(®) technology (Illumina, CA, USA). We describe the coverage of the methylome by this technique. Several examples of data mining are provided. However, it should be understood that reliance on a single aspect of epigenetics has its limitations. In the not too distant future, these defects may be rectified, providing scientists with previously unavailable opportunities to explore in detail the role of epigenetics in cancer and other disease states.

Genomic and transcriptional alterations in lung adenocarcinoma in relation to EGFR and KRAS mutation status

Introduction

In lung adenocarcinoma, the mutational spectrum is dominated by EGFR and KRAS mutations. Improved knowledge about genomic and transcriptional alterations in and between mutation-defined subgroups may identify genes involved in disease development or progression.

Methods

Genomic profiles from 457 adenocarcinomas, including 113 EGFR-mutated, 134 KRAS-mutated and 210 EGFR and KRAS-wild type tumors (EGFRwt/KRASwt), and gene expression profiles from 914 adenocarcinomas, including 309 EGFR-mutated, 192 KRAS-mutated, and 413 EGFRwt/KRASwt tumors, were assembled from different repositories. Genomic and transcriptional differences between the three mutational groups were analyzed by both supervised and unsupervised methods.

Results

EGFR-mutated adenocarcinomas displayed a larger number of copy number alterations and recurrent amplifications, a higher fraction of total loss-of-heterozygosity, higher genomic complexity, and a more distinct expression pattern than EGFR-wild type adenocarcinomas. Several of these differences were also consistent when the three mutational groups were stratified by stage, gender and smoking status. Specific copy number alterations were associated with mutation status, predominantly including regions of gain with the highest frequency in EGFR-mutated tumors. Differential regions included both large and small regions of gain on 1p, 5q34-q35.3, 7p, 7q11.21, 12p12.1, 16p, and 21q, and losses on 6q16.3-q21, 8p, and 9p, with 20-40% frequency differences between the mutational groups. Supervised gene expression analyses identified 96 consistently differentially expressed genes between the mutational groups, and together with unsupervised analyses these analyses highlighted the difficulty in broadly resolving the three mutational groups into distinct transcriptional entities.

Conclusions

We provide a comprehensive overview of the genomic and transcriptional landscape in lung adenocarcinoma stratified by EGFR and KRAS mutations. Our analyses suggest that the overall genomic and transcriptional landscape of lung adenocarcinoma is affected, but only to a minor extent, by EGFR and KRAS mutation status.

EYA4 is inactivated biallelically at a high frequency in sporadic lung cancer and is associated with familial lung cancer risk

In an effort to identify novel biallelically inactivated tumor suppressor genes (TSG) in sporadic invasive and pre-invasive non-small cell lung cancer (NSCLC) genomes, we applied a comprehensive integrated multi-‘omics approach to investigate patient matched, paired NSCLC tumor and non-malignant parenchymal tissues. By surveying lung tumor genomes for genes concomitantly inactivated within individual tumors by multiple mechanisms, and by the frequency of disruption in tumors across multiple cohorts, we have identified a putative lung cancer TSG, Eyes Absent 4 (EYA4). EYA4 is frequently and concomitantly deleted, hypermethylated and underexpressed in multiple independent lung tumor data sets, in both major NSCLC subtypes, and in the earliest stages of lung cancer. We find not only that decreased EYA4 expression is associated with poor survival in sporadic lung cancers, but EYA4 SNPs are associated with increased familial cancer risk, consistent with EYA4’s proximity to the previously reported lung cancer susceptibility locus on 6q. Functionally, we find that EYA4 displays TSG-like properties with a role in modulating apoptosis and DNA repair. Cross examination of EYA4 expression across multiple tumor types suggests a cell type-specific tumorigenic role for EYA4, consistent with a tumor suppressor function in cancers of epithelial origin. This work shows a clear role for EYA4 as a putative TSG in NSCLC.

A prognostic DNA methylation signature for stage I non-small-cell lung cancer

PURPOSE

Non-small-cell lung cancer (NSCLC) is a tumor in which only small improvements in clinical outcome have been achieved. The issue is critical for stage I patients for whom there are no available biomarkers that indicate which high-risk patients should receive adjuvant chemotherapy. We aimed to find DNA methylation markers that could be helpful in this regard.

PATIENTS AND METHODS

A DNA methylation microarray that analyzes 450,000 CpG sites was used to study tumoral DNA obtained from 444 patients with NSCLC that included 237 stage I tumors. The prognostic DNA methylation markers were validated by a single-methylation pyrosequencing assay in an independent cohort of 143 patients with stage I NSCLC.

RESULTS

Unsupervised clustering of the 10,000 most variable DNA methylation sites in the discovery cohort identified patients with high-risk stage I NSCLC who had shorter relapse-free survival (RFS; hazard ratio [HR], 2.35; 95% CI, 1.29 to 4.28; P = .004). The study in the validation cohort of the significant methylated sites from the discovery cohort found that hypermethylation of five genes was significantly associated with shorter RFS in stage I NSCLC: HIST1H4F, PCDHGB6, NPBWR1, ALX1, and HOXA9. A signature based on the number of hypermethylated events distinguished patients with high- and low-risk stage I NSCLC (HR, 3.24; 95% CI, 1.61 to 6.54; P = .001).

CONCLUSION

The DNA methylation signature of NSCLC affects the outcome of stage I patients, and it can be practically determined by user-friendly polymerase chain reaction assays. The analysis of the best DNA methylation biomarkers improved prognostic accuracy beyond standard staging.

Detection and quantification of methylation in DNA using solid-state nanopores

Epigenetic modifications in eukaryotic genomes occur primarily in the form of 5-methylcytosine (5 mC). These modifications are heavily involved in transcriptional repression, gene regulation, development and the progression of diseases including cancer. We report a new single-molecule assay for the detection of DNA methylation using solid-state nanopores. Methylation is detected by selectively labeling methylation sites with MBD1 (MBD-1x) proteins, the complex inducing a 3 fold increase in ionic blockage current relative to unmethylated DNA. Furthermore, the discrimination of methylated and unmethylated DNA is demonstrated in the presence of only a single bound protein, thereby giving a resolution of a single methylated CpG dinucleotide. The extent of methylation of a target molecule could also be coarsely quantified using this novel approach. This nanopore-based methylation sensitive assay circumvents the need for bisulfite conversion, fluorescent labeling, and PCR and could therefore prove very useful in studying the role of epigenetics in human disease.

Genetic alterations defining NSCLC subtypes and their therapeutic implications

Lung cancer is the leading cause of cancer death worldwide, accounting for more deaths than breast, prostate and colon cancer combined. While treatment decisions are determined primarily by stage, therapeutically non small cell lung cancer (NSCLC) has traditionally been treated as a single disease. However, recent findings have led to the recognition of histology and molecular subtypes as important determinants in treatment selection. Identifying the genetic differences that define these molecular and histological subtypes has the potential to impact treatment and as such is currently the focus of much research. Microarray and genomic sequencing efforts have provided unparalleled insight into the genomes of lung cancer subtypes, specifically adenocarcinoma (AC) and squamous cell carcinoma (SqCC), revealing subtype specific genomic alterations and molecular subtypes as well as differences in cell signaling pathways. In this review, we discuss the recurrent genomic alterations characteristic of AC and SqCC (including molecular subtypes), their therapeutic implications and emerging clinical practices aimed at tailoring treatments based on a tumor's molecular alterations with the hope of improving patient response and survival.

Lung cancer epigenetics: emerging biomarkers

Lung cancer is the leading cause of cancer-related deaths worldwide, and the 5-year survival rate is still very poor due to the scarcity of effective tools for early detection. The discovery of highly sensitive and specific biomarkers highlighting pathological changes early enough to allow clinical intervention is therefore of great importance. In the last decade, epigenetics and particularly research on DNA methylation have provided important information towards a better understanding of lung cancer pathogenesis. Novel and promising molecular biomarkers for diagnosis and prognosis of lung cancer are continuously emerging in this area, requiring further evaluation. This process includes extensive validation in prospective clinical trials before they can be routinely used in a clinical setting. This review summarizes the evidence on epigenetic biomarkers for lung cancer, focusing on DNA methylation.

Age-associated epigenetic drift: implications, and a case of epigenetic thrift?

It is now well established that the genomic landscape of DNA methylation (DNAm) gets altered as a function of age, a process we here call ‘epigenetic drift’. The biological, functional, clinical and evolutionary significance of this epigenetic drift, however, remains unclear. We here provide a brief review of epigenetic drift, focusing on the potential implications for ageing, stem cell biology and disease risk prediction. It has been demonstrated that epigenetic drift affects most of the genome, suggesting a global deregulation of DNAm patterns with age. A component of this drift is tissue-specific, allowing remarkably accurate age-predictive models to be constructed. Another component is tissue-independent, targeting stem cell differentiation pathways and affecting stem cells, which may explain the observed decline of stem cell function with age. Age-associated increases in DNAm target developmental genes, overlapping those associated with environmental disease risk factors and with disease itself, notably cancer. In particular, cancers and precursor cancer lesions exhibit aggravated age DNAm signatures. Epigenetic drift is also influenced by genetic factors. Thus, drift emerges as a promising biomarker for premature or biological ageing, and could potentially be used in geriatrics for disease risk prediction. Finally, we propose, in the context of human evolution, that epigenetic drift may represent a case of epigenetic thrift, or bet-hedging. In summary, this review demonstrates the growing importance of the ‘ageing epigenome’, with potentially far-reaching implications for understanding the effect of age on stem cell function and differentiation, as well as for disease prevention.

Epigenetic therapy in non-small-cell lung cancer: targeting DNA methyltransferases and histone deacetylases

INTRODUCTION

Epigenetics refers to heritable modifications of DNA and associated chromatin components that influence gene expression without altering DNA coding sequence. Epigenetic dysregulation is a central contributor to oncogenesis and is increasingly a focus of interest in cancer therapeutic research. Two key levels of aberrant epigenetic control are DNA methylation and histone acetylation. Primary regulators of these epigenetic changes include DNA methyltransferases (DNMTs) and histone deacetylases (HDACs).

AREAS COVERED

This review focuses on epigenetic changes in non-small-cell lung cancer and recent preclinical and clinical studies targeting these changes. DNMT inhibitors were previously explored at or near maximally tolerated doses, levels at which these agents are cytotoxic but have suboptimal effects on DNA methylation. Use of these inhibitors at substantially lower doses, in combination with HDAC inhibitors, can promote re-expression of silenced tumor suppressor genes, can result in major clinical responses and may alter tumor responsiveness to subsequent cytotoxic therapies.

EXPERT OPINION

Combinatorial epigenetic therapy has demonstrated encouraging clinical activity, but many relevant questions remain. Global strategies influencing the epigenome may have both positive and potential negative long-term effects on cancer progression. Further clinical investigation of this approach, including exploratory studies to define predictive biomarkers, is warranted.