DNA hypermethylation in lung cancer is targeted at differentiation-associated genes

Fast proliferating and slowly migrating non-small cell lung cancer cells are vulnerable to decitabine and retinoic acid combinatorial treatment

Non-small cell lung cancer (NSCLC) patients are often elderly or unfit and thus cannot tolerate standard aggressive therapy regimes. In our study, we test the efficacy of the DNA-hypomethylating agent decitabine (DAC) in combination with all-trans retinoic acid (ATRA), which has been shown to possess little systemic adverse effects. Screening a broad panel of 56 NSCLC cell lines uncovered a decrease in cell viability after the combination treatment in 77% of the cell lines. Transcriptomics, proteomics, proliferation and migration profiling revealed that fast proliferating and slowly migrating cell lines were more sensitive to the drug combination. The comparison of mutational profiles found oncogenic KRAS mutations only in sensitive cells. Additionally, different cell lines showed a heterogeneous gene expression response to the treatment pointing to diverse mechanisms of action. Silencing KRAS, RIG-I or RARB partially reversed the sensitivity of KRAS-mutant NCI-H460 cells. To study resistance, we generated two NCI-H460 cell populations resistant to ATRA and DAC, which migrated faster and proliferated slower than the parental sensitive cells and showed signs of senescence. In summary, this comprehensive dataset uncovers a broad sensitivity of NSCLC cells to the combinatorial treatment with DAC and ATRA and indicates that migration and proliferation capacities correlate with and could thus serve as determinants for drug sensitivity in NSCLC.

Comprehensive Analyses Revealed Eight Immune Related Signatures Correlated With Aberrant Methylations as Prognosis and Diagnosis Biomarkers for Kidney Renal Papillary Cell Carcinoma

BACKGROUND

Kidney renal papillary cell carcinoma (KIRP) is a common type of renal cell carcinoma. DNA methylation plays an important role in the development of several cancers. The aim of our study was to identify differentially expressed genes associated with abnormal DNA methylation as biomarkers for predicting the outcome of KIRP.

METHOD

We downloaded KIRP methylation data, RNA sequencing (RNAseq) data, and their corresponding clinical information from the Cancer Genome Atlas (TCGA) database. ChAMP and DEGseq2 packages in R software were used to screen differentially methylated probes (DMPs) and differentially expressed genes (DEGs). Univariate and multivariate Cox regression analyses were used to identify suitable immune related genes correlated with aberrant methylations as prognosis biomarkers.

RESULTS

We identified 8 DEGs (Cysteine And Glycine Rich Protein 1 [CSRP1], major histocompatibility complex, Class II, DM Beta [HLA-DMB], LIF Receptor Subunit Alpha [LIFR], Leukotriene B4 receptor 2 [LTB4R2], Mitogen-Activated Protein Kinase Kinase Kinase 14 [MAP3K14], Nuclear Receptor Subfamily 2 Group F Member 1 [NR2F1], Secreted And Transmembrane 1 [SECTM1], and Vimentin [VIM]) that were independently associated with the overall survival (months) (OS) of KIRP. The time dependent area under the curve (AUC) for each receiver operating characteristic (ROC) of the risk assessment model at 1, 3, 5, and 10-years reached 0.8415, 0.8131, 0.7873, and 0.7667. The risk assessment model was correlated with several immune cells and factors. The AUC value of the diagnosis model using those 8 DEGs reached 0.99.

CONCLUSIONS

The risk assessment model constructed by those 8 DEGs was well able to predict the prognosis and diagnose of KIRP. However, whether the prognosis and diagnosis model could be applied in clinical practice requires further study.

Synergies of Radiomics and Transcriptomics in Lung Cancer Diagnosis: A Pilot Study

Radiotranscriptomics is an emerging field that aims to investigate the relationships between the radiomic features extracted from medical images and gene expression profiles that contribute in the diagnosis, treatment planning, and prognosis of cancer. This study proposes a methodological framework for the investigation of these associations with application on non-small-cell lung cancer (NSCLC). Six publicly available NSCLC datasets with transcriptomics data were used to derive and validate a transcriptomic signature for its ability to differentiate between cancer and non-malignant lung tissue. A publicly available dataset of 24 NSCLC-diagnosed patients, with both transcriptomic and imaging data, was used for the joint radiotranscriptomic analysis. For each patient, 749 Computed Tomography (CT) radiomic features were extracted and the corresponding transcriptomics data were provided through DNA microarrays. The radiomic features were clustered using the iterative K-means algorithm resulting in 77 homogeneous clusters, represented by meta-radiomic features. The most significant differentially expressed genes (DEGs) were selected by performing Significance Analysis of Microarrays (SAM) and 2-fold change. The interactions among the CT imaging features and the selected DEGs were investigated using SAM and a Spearman rank correlation test with a False Discovery Rate (FDR) of 5%, leading to the extraction of 73 DEGs significantly correlated with radiomic features. These genes were used to produce predictive models of the meta-radiomics features, defined as p-metaomics features, by performing Lasso regression. Of the 77 meta-radiomic features, 51 can be modeled in terms of the transcriptomic signature. These significant radiotranscriptomics relationships form a reliable basis to biologically justify the radiomics features extracted from anatomic imaging modalities. Thus, the biological value of these radiomic features was justified via enrichment analysis on their transcriptomics-based regression models, revealing closely associated biological processes and pathways. Overall, the proposed methodological framework provides joint radiotranscriptomics markers and models to support the connection and complementarities between the transcriptome and the phenotype in cancer, as demonstrated in the case of NSCLC.

DNA methylation perturbations may link altered development and aging in the lung

Fetal perturbations in DNA methylation during lung development may reveal insights into the enduring impacts on adult lung health and disease during aging that have not been explored altogether before. We studied the association between genome-wide DNA-methylation and post-conception age in fetal-lung (n=78, 42 exposed to in-utero-smoke (IUS)) tissue and chronological age in adult-lung tissue (n=160, 114 with Chronic Obstructive Pulmonary Disease) using multi-variate linear regression models with covariate adjustment and tested for effect modification by phenotypes. Overlapping age-associations were evaluated for functional and tissue-specific enrichment using the Genotype-Tissue-Expression (GTEx) project. We identified 244 age-associated differentially methylated positions and 878 regions overlapping between fetal and adult-lung tissues. Hyper-methylated CpGs (96%) were enriched in transcription factor activity (FDR adjusted P=2x10^-33) and implicated in developmental processes including embryonic organ morphogenesis, neurogenesis and growth delay. Hypo-methylated CpGs (2%) were enriched in oxido-reductase activity and VEGFA-VEGFR2 Signaling. Twenty-one age-by-sex and eleven age-by-pack-years interactions were statistically significant (FDR<0.05) in adult-lung tissue. DNA methylation in transcription factors during development in fetal lung recapitulates in adult-lung tissue with aging. These findings reveal molecular mechanisms and pathways that may link disrupted development in early-life and age-associated lung diseases.

Correlation between EZH2 and CEP55 and lung adenocarcinoma prognosis

OBJECTIVE

Recently, accumulated evidence indicates that the enhancer of zeste homologue 2 (EZH2) is highly expressed in a wide range of cancer types, including NSCLC. The downstream genes regulated by EZH2 were screened using bioinformatics analysis. This study aimed to analyse the correlation between the downstream genes of EZH2 and the prognosis of lung adenocarcinoma.

METHODS

Expression and methylation data of lung adenocarcinoma were downloaded from The Cancer Genome Atlas (TCGA) (https://cancergenome.nih.gov/) database, and data were categorized into EZH2 overexpression and EZH2 downregulation groups according to EZH2 expression. The genes that showed opposite trends of methylation and expression changes were screened, and the association of gene expression was calculated. Based on the String database, a protein association analysis was conducted to identify genes related to EZH2, which are referred to as EZH2 regulation candidate genes. According to gene expression (GSE27262) and methylation (GSE66836) chip data in the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) database, the genes with differential expression and methylation in lung adenocarcinoma tissues were analysed, and the trends of EZH2 regulation candidate gene expression and methylation were verified to identify the EZH2 regulation candidate genes. Subsequently, MethHC (http://methhc.mbc.nctu.edu.tw/php/index.php) and UALCAN (http://ualcan.path.uab.edu/index.html) were employed to verify changes in the expression and methylation of EZH2 downstream regulation candidate genes and to analyse the correlation between these genes and the prognosis of lung adenocarcinoma.

RESULTS

Expression and methylation data of lung adenocarcinoma were downloaded from TCGA database and categorized into EZH2 overexpression and EZH2 downregulation groups according to EZH2 expression. A total of 337 genes that showed opposite trends of methylation and expression changes were obtained. The protein association analysis using the String (https://string-db.org/) database showed that 61 genes interact with EZH2 and 61 genes represent EZH2 downstream regulation candidate genes. Moreover, 222 genes obtained from GSE27262 and GSE66836 chip data were negatively correlated with methylation and expression changes, and centrosomal protein 55 (CEP55) was identified as the EZH2 downstream regulation candidate gene. CEP55 was upregulated in lung adenocarcinoma tissues and showed low methylation. According to gene expression data from TCGA database, CEP55 and EZH2 exhibit higher levels in lung adenocarcinoma tissue than in adjacent normal tissue. Finally, the survival analysis revealed that EZH2 is not associated with the prognosis of lung adenocarcinoma, while CEP55 is related to lung adenocarcinoma prognosis.

CONCLUSION

Taken together, these results indicate that changes in EZH2 expression lead to changes in CEP55 expression in lung adenocarcinoma, and these changes are associated with its prognosis.

Air pollution and DNA methylation alterations in lung cancer: A systematic and comparative study

The lung cancer incidence in the Xuanwei and neighboring region, Yunnan, China, is among the highest in China and is attributed to severe air pollution with high benzo(a)pyrene levels. We systematically and comparatively analyzed DNA methylation alterations at genome and gene levels in Xuanwei lung cancer tissues and cell lines, as well as benzo(a)pyrene-treated cells and mouse samples. We obtained a comprehensive dataset of genome-wide cytosine-phosphate-guanine island methylation in air pollution-related lung cancer samples. Benzo(a)pyrene exposure induced multiple alterations in DNA methylation and in mRNA expressions of DNA methyltransferases and ten-11 translocation proteins; these alterations partially occurred in Xuanwei lung cancer. Furthermore, benzo(a)pyrene-induced DKK2 and EN1 promoter hypermethylation and LPAR2 promoter hypomethylation led to down-regulation and up-regulation of the genes, respectively; the down-regulation of DKK2 and EN1 promoted the cellular proliferation. Thus, DNA methylation alterations induced by benzo(a)pyrene contribute partially to abnormal DNA methylation in air pollution-related lung cancer, and these DNA methylation alterations may affect the development and progression of lung cancer. Additionally, vitamin C and B6 can reduce benzo(a)pyrene-induced DNA methylation alterations and may be used as chemopreventive agents for air pollution-related lung cancer.

Differences in MWCNT- and SWCNT-induced DNA methylation alterations in association with the nuclear deposition

BACKGROUND

Subtle DNA methylation alterations mediated by carbon nanotubes (CNTs) exposure might contribute to pathogenesis and disease susceptibility. It is known that both multi-walled carbon nanotubes (MWCNTs) and single-walled carbon nanotubes (SWCNTs) interact with nucleus. Such, nuclear-CNT interaction may affect the DNA methylation effects. In order to understand the epigenetic toxicity, in particular DNA methylation alterations, of SWCNTs and short MWCNTs, we performed global/genome-wide, gene-specific DNA methylation and RNA-expression analyses after exposing human bronchial epithelial cells (16HBE14o- cell line). In addition, the presence of CNTs on/in the cell nucleus was evaluated in a label-free way using femtosecond pulsed laser microscopy.

RESULTS

Generally, a higher number of SWCNTs, compared to MWCNTs, was deposited at both the cellular and nuclear level after exposure. Nonetheless, both CNT types were in physical contact with the nuclei. While particle type dependency was noticed for the identified genome-wide and gene-specific alterations, no global DNA methylation alteration on 5-methylcytosine (5-mC) sites was observed for both CNTs. After exposure to MWCNTs, 2398 genes were hypomethylated (at gene promoters), and after exposure to SWCNTs, 589 CpG sites (located on 501 genes) were either hypo- (N = 493 CpG sites) or hypermethylated (N = 96 CpG sites). Cells exposed to MWCNTs exhibited a better correlation between gene promoter methylation and gene expression alterations. Differentially methylated and expressed genes induced changes (MWCNTs > SWCNTs) at different cellular pathways, such as p53 signalling, DNA damage repair and cell cycle. On the other hand, SWCNT exposure showed hypermethylation on functionally important genes, such as SKI proto-oncogene (SKI), glutathione S-transferase pi 1 (GTSP1) and shroom family member 2 (SHROOM2) and neurofibromatosis type I (NF1), which the latter is both hypermethylated and downregulated.

CONCLUSION

After exposure to both types of CNTs, epigenetic alterations may contribute to toxic or repair response. Moreover, our results suggest that the observed differences in the epigenetic response depend on particle type and differential CNT-nucleus interactions.

Chronic Cigarette Smoke-Induced Epigenomic Changes Precede Sensitization of Bronchial Epithelial Cells to Single-Step Transformation by KRAS Mutations

We define how chronic cigarette smoke-induced time-dependent epigenetic alterations can sensitize human bronchial epithelial cells for transformation by a single oncogene. The smoke-induced chromatin changes include initial repressive polycomb marking of genes, later manifesting abnormal DNA methylation by 10 months. At this time, cells exhibit epithelial-to-mesenchymal changes, anchorage-independent growth, and upregulated RAS/MAPK signaling with silencing of hypermethylated genes, which normally inhibit these pathways and are associated with smoking-related non-small cell lung cancer. These cells, in the absence of any driver gene mutations, now transform by introducing a single KRAS mutation and form adenosquamous lung carcinomas in mice. Thus, epigenetic abnormalities may prime for changing oncogene senescence to addiction for a single key oncogene involved in lung cancer initiation.

A prospective study of tumor suppressor gene methylation as a prognostic biomarker in surgically resected stage I to IIIA non-small-cell lung cancers

INTRODUCTION

While retrospective analyses support an association between early tumor recurrence and tumor suppressor gene promoter methylation in early-stage non-small-cell lung cancers (NSCLCs), few studies have investigated this question prospectively.

METHODS

Primary tumor tissue from patients with resected pathologic stage I to IIIA NSCLCs was collected at the time of surgery and analyzed for promoter methylation via methylation-specific reverse transcriptase polymerase chain reaction (MethyLight). The primary objective was to determine an association between promoter methylation of 10 individual tumor suppressor genes (CDKN2A, CDH13, RASSF1, APC, MGMT, GSTP1, DAPK1, WIF1, SOCS3, and ADAMTS8) and recurrence-free survival (RFS), with the secondary objectives of determining association with overall survival (OS), and relation to clinical or pathologic features.

RESULTS

A total of 107 patients had sufficient tumor tissue for successful promoter methylation analysis. Majority of patients were former/current smokers (88%) with lung adenocarcinoma (78%) and pathologic stage I disease (62%). Median follow-up was 4 years. When controlled for pathologic stage, promoter methylation of the individual genes CDKN2A, CDH13, RASSF1, APC, MGMT, GSTP1, DAPK1, WIF1, and ADAMTS8 was not associated with RFS. Promoter methylation of the same genes was not associated with OS except for DAPK1 which was associated with improved OS (p = 0.03). The total number of genes with methylated promoters did not correlate with RFS (p = 0.89) or OS (p = 0.55).

CONCLUSION

Contrary to data established by previous retrospective series, tumor suppressor gene promoter methylation (CDKN2A, CDH13, RASSF1, APC, MGMT, GSTP1, DAPK1, WIF1, and ADAMTS8) was not prognostic for early tumor recurrence in this prospective study of resected NSCLCs.

Systems biology of cancer: entropy, disorder, and selection-driven evolution to independence, invasion and "swarm intelligence"

Our knowledge of the biology of solid cancer has greatly progressed during the last few years, and many excellent reviews dealing with the various aspects of this biology have appeared. In the present review, we attempt to bring together these subjects in a general systems biology narrative. It starts from the roles of what we term entropy of signaling and noise in the initial oncogenic events, to the first major transition of tumorigenesis: the independence of the tumor cell and the switch in its physiology, i.e., from subservience to the organism to its own independent Darwinian evolution. The development after independence involves a constant dynamic reprogramming of the cells and the emergence of a sort of collective intelligence leading to invasion and metastasis and seldom to the ultimate acquisition of immortality through inter-individual infection. At each step, the probability of success is minimal to infinitesimal, but the number of cells possibly involved and the time scale account for the relatively high occurrence of tumorigenesis and metastasis in multicellular organisms.

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.

High-frequency aberrantly methylated targets in pancreatic adenocarcinoma identified via global DNA methylation analysis using methylCap-seq

BACKGROUND

Extensive reprogramming and dysregulation of DNA methylation is an important characteristic of pancreatic cancer (PC). Our study aimed to characterize the genomic methylation patterns in various genomic contexts of PC. The methyl capture sequencing (methylCap-seq) method was used to map differently methylated regions (DMRs) in pooled samples from ten PC tissues and ten adjacent non-tumor (PN) tissues. A selection of DMRs was validated in an independent set of PC and PN samples using methylation-specific PCR (MSP), bisulfite sequencing PCR (BSP), and methylation sensitive restriction enzyme-based qPCR (MSRE-qPCR). The mRNA and expressed sequence tag (EST) expression of the corresponding genes was investigated using RT-qPCR.

RESULTS

A total of 1,131 PC-specific and 727 PN-specific hypermethylated DMRs were identified in association with CpG islands (CGIs), including gene-associated CGIs and orphan CGIs; 2,955 PC-specific and 2,386 PN-specific hypermethylated DMRs were associated with gene promoters, including promoters containing or lacking CGIs. Moreover, 1,744 PC-specific and 1,488 PN-specific hypermethylated DMRs were found to be associated with CGIs or CGI shores. These results suggested that aberrant hypermethylation in PC typically occurs in regions surrounding the transcription start site (TSS). The BSP, MSP, MSRE-qPCR, and RT-qPCR data indicated that the aberrant DNA methylation in PC tissue and in PC cell lines was associated with gene (or corresponding EST) expression.

CONCLUSIONS

Our study characterized the genome-wide DNA methylation patterns in PC and identified DMRs that were distributed among various genomic contexts that might influence the expression of corresponding genes or transcripts to promote PC. These DMRs might serve as diagnostic biomarkers or therapeutic targets for PC.

Selective HDAC1/HDAC2 inhibitors induce neuroblastoma differentiation

While cytotoxic chemotherapy remains the hallmark of cancer treatment, intensive regimens fall short in many malignancies, including high-risk neuroblastoma. One alternative strategy is to therapeutically promote tumor differentiation. We created a gene expression signature to measure neuroblast maturation, adapted it to a high-throughput platform, and screened a diversity oriented synthesis-generated small-molecule library for differentiation inducers. We identified BRD8430, containing a nine-membered lactam, an ortho-amino anilide functionality, and three chiral centers, as a selective class I histone deacetylase (HDAC) inhibitor (HDAC1 > 2 > 3). Further investigation demonstrated that selective HDAC1/HDAC2 inhibition using compounds or RNA interference induced differentiation and decreased viability in neuroblastoma cell lines. Combined treatment with 13-cis retinoic acid augmented these effects and enhanced activation of retinoic acid signaling. Therefore, by applying a chemical genomic screening approach, we identified selective HDAC1/HDAC2 inhibition as a strategy to induce neuroblastoma differentiation.

Real-time methylomic aberrations during initiation and progression of induced human mammary epithelial cell tumorigenesis

AIM

Neoplastic transformation provides one of the few existing opportunities to analyze molecular changes in real time during the initiation and progression of breast cancer.

MATERIALS & METHODS

Human mammary epithelial cells underwent neoplastic reprogramming, generating one line of semitransformed, premalignant cells and two separate, temporal lines of fully transformed human mammary epithelial cells (THMECs). An Illumina Infinium HumanMethylation27 BeadChip was used to analyze DNA methylation alterations in 27,578 CpG loci at three consecutive time points over an 80-day (d) transformation period.

RESULTS

The mean β value for semitransformed human mammary epithelial cells CpG loci (0.245) was much greater than for either THMEC-40d (0.055) or THMEC-80d (0.066), indicating a large loss of methylation after neoplastic induction. In addition, 54% of CpG loci were hypermethylated during the THMEC-40d to THMEC-80d transition. We observed that the CpG loci exhibiting DNA methylation changes during early oncogenesis were enriched for biological functions like cellular movement; this was distinctly different than in the later, more progressive stages of the transformation process enriched for processes involving differentiation.

CONCLUSION

The timing of major methylomic changes may be important in directing the cell toward a more cancerous phenotype. In addition, gene-specific hypermethylation appears to silence developmentally related genes, leading to dedifferentiation.

DNA methylation signatures identify biologically distinct thyroid cancer subtypes

OBJECTIVE

The purpose of this study was to determine the global patterns of aberrant DNA methylation in thyroid cancer.

RESEARCH DESIGN AND METHODS

We have used DNA methylation arrays to determine, for the first time, the genome-wide promoter methylation status of papillary, follicular, medullary, and anaplastic thyroid tumors.

RESULTS

We identified 262 and 352 hypermethylated and 13 and 21 hypomethylated genes in differentiated papillary and follicular tumors, respectively. Interestingly, the other tumor types analyzed displayed more hypomethylated genes (280 in anaplastic and 393 in medullary tumors) than aberrantly hypermethylated genes (86 in anaplastic and 131 in medullary tumors). Among the genes indentified, we show that 4 potential tumor suppressor genes (ADAMTS8, HOXB4, ZIC1, and KISS1R) and 4 potential oncogenes (INSL4, DPPA2, TCL1B, and NOTCH4) are frequently regulated by aberrant methylation in primary thyroid tumors. In addition, we show that aberrant promoter hypomethylation-associated overexpression of MAP17 might promote tumor growth in thyroid cancer.

CONCLUSIONS

Thyroid cancer subtypes present differential promoter methylation signatures, and nondifferentiated subtypes are characterized by aberrant promoter hypomethylation rather than hypermethylation. Additional studies are needed to determine the potential clinical interest of the tumor subtype-specific DNA methylation signatures described herein and the role of aberrant promoter hypomethylation in nondifferentiated thyroid tumors.

Gene-set analysis is severely biased when applied to genome-wide methylation data

MOTIVATION

DNA methylation is an epigenetic mark that can stably repress gene expression. Because of its biological and clinical significance, several methods have been developed to compare genome-wide patterns of methylation between groups of samples. The application of gene set analysis to identify relevant groups of genes that are enriched for differentially methylated genes is often a major component of the analysis of these data. This can be used, for example, to identify processes or pathways that are perturbed in disease development. We show that gene-set analysis, as it is typically applied to genome-wide methylation assays, is severely biased as a result of differences in the numbers of CpG sites associated with different classes of genes and gene promoters.

RESULTS

We demonstrate this bias using published data from a study of differential CpG island methylation in lung cancer and a dataset we generated to study methylation changes in patients with long-standing ulcerative colitis. We show that several of the gene sets that seem enriched would also be identified with randomized data. We suggest two existing approaches that can be adapted to correct the bias. Accounting for the bias in the lung cancer and ulcerative colitis datasets provides novel biological insights into the role of methylation in cancer development and chronic inflammation, respectively. Our results have significant implications for many previous genome-wide methylation studies that have drawn conclusions on the basis of such strongly biased analysis.

CONTACT

cathal.seoighe@nuigalway.ie

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genomic insights into cancer-associated aberrant CpG island hypermethylation

Carcinogenesis is thought to occur through a combination of mutational and epimutational events that disrupt key pathways regulating cellular growth and division. The DNA methylomes of cancer cells can exhibit two striking differences from normal cells; a global reduction of DNA methylation levels and the aberrant hypermethylation of some sequences, particularly CpG islands (CGIs). This aberrant hypermethylation is often invoked as a mechanism causing the transcriptional inactivation of tumour suppressor genes that directly drives the carcinogenic process. Here, we review our current understanding of this phenomenon, focusing on how global analysis of cancer methylomes indicates that most affected CGI genes are already silenced prior to aberrant hypermethylation during cancer development. We also discuss how genome-scale analyses of both normal and cancer cells have refined our understanding of the elusive mechanism(s) that may underpin aberrant CGI hypermethylation.

Epigenome remodelling in breast cancer: insights from an early in vitro model of carcinogenesis

Epigenetic gene regulation has influence over a diverse range of cellular functions, including the maintenance of pluripotency, differentiation, and cellular identity, and is deregulated in many diseases, including cancer. Whereas the involvement of epigenetic dysregulation in cancer is well documented, much of the mechanistic detail involved in triggering these changes remains unclear. In the current age of genomics, the development of new sequencing technologies has seen an influx of genomic and epigenomic data and drastic improvements in both resolution and coverage. Studies in cancer cell lines and clinical samples using next-generation sequencing are rapidly delivering spectacular insights into the nature of the cancer genome and epigenome. Despite these improvements in technology, the timing and relationship between genetic and epigenetic changes that occur during the process of carcinogenesis are still unclear. In particular, what changes to the epigenome are playing a driving role during carcinogenesis and what influence the temporal nature of these changes has on cancer progression are not known. Understanding the early epigenetic changes driving breast cancer has the exciting potential to provide a novel set of therapeutic targets or early-disease biomarkers or both. Therefore, it is important to find novel systems that permit the study of initial epigenetic events that potentially occur during the first stages of breast cancer. Non-malignant human mammary epithelial cells (HMECs) provide an exciting in vitro model of very early breast carcinogenesis. When grown in culture, HMECs are able to temporarily escape senescence and acquire a pre-malignant breast cancer-like phenotype (variant HMECs, or vHMECs). Cultured HMECs are composed mainly of cells from the basal breast epithelial layer. Therefore, vHMECs are considered to represent the basal-like subtype of breast cancer. The transition from HMECs to vHMECs in culture recapitulates the epigenomic phenomena that occur during the progression from normal breast to pre-malignancy. Therefore, the HMEC model system provides the unique opportunity to study the very earliest epigenomic aberrations occurring during breast carcinogenesis and can give insight into the sequence of epigenomic events that lead to breast malignancy. This review provides an overview of epigenomic research in breast cancer and discusses in detail the utility of the HMEC model system to discover early epigenomic changes involved in breast carcinogenesis.

Reversal of aberrant cancer methylome and transcriptome upon direct reprogramming of lung cancer cells

Recent reports on direct reprogramming of cancer cells (iPCs) which results in reduced tumorigenic potential has attributed the importance of epigenetics in tumorigenesis, but lacked genome-wide analysis. Here we describe successful generation of iPCs from non-small cell lung cancer (NSCLC) cell lines. Following reprogramming, they resembled embryonic stem and induced pluripotent stem cells in pluripotency markers expression, gene expression patterns and in vitro differentiation ability. Genome-wide methylation analysis revealed that aberrantly methylated promoters which were mostly developmental-associated genes and tumor suppressors; as well as commonly upregulated genes in NSCLC i.e. KRT19 and S100P were reversed in iPCs upon reprogramming. Also, the reversal of oncogenes and tumor suppressors status were partially explainable by DNA methylation. These findings suggest that DNA methylation patterns explain the downstream transcriptional effects, which potentially caused the reduced tumorigenicity in iPCs, thus providing evidence that reprogramming reverses the aberrantly dysregulated genes in NSCLC both epigenetically and transcriptionally.

Genome-wide DNA methylation profiling of non-small cell lung carcinomas

Background

Non-small cell lung carcinoma (NSCLC) is a complex malignancy that owing to its heterogeneity and poor prognosis poses many challenges to diagnosis, prognosis and patient treatment. DNA methylation is an important mechanism of epigenetic regulation involved in normal development and cancer. It is a very stable and specific modification and therefore in principle a very suitable marker for epigenetic phenotyping of tumors. Here we present a genome-wide DNA methylation analysis of NSCLC samples and paired lung tissues, where we combine MethylCap and next generation sequencing (MethylCap-seq) to provide comprehensive DNA methylation maps of the tumor and paired lung samples. The MethylCap-seq data were validated by bisulfite sequencing and methyl-specific polymerase chain reaction of selected regions.

Results

Analysis of the MethylCap-seq data revealed a strong positive correlation between replicate experiments and between paired tumor/lung samples. We identified 57 differentially methylated regions (DMRs) present in all NSCLC tumors analyzed by MethylCap-seq. While hypomethylated DMRs did not correlate to any particular functional category of genes, the hypermethylated DMRs were strongly associated with genes encoding transcriptional regulators. Furthermore, subtelomeric regions and satellite repeats were hypomethylated in the NSCLC samples. We also identified DMRs that were specific to two of the major subtypes of NSCLC, adenocarcinomas and squamous cell carcinomas.

Conclusions

Collectively, we provide a resource containing genome-wide DNA methylation maps of NSCLC and their paired lung tissues, and comprehensive lists of known and novel DMRs and associated genes in NSCLC.

Chronic occupational exposure to arsenic induces carcinogenic gene signaling networks and neoplastic transformation in human lung epithelial cells

Chronic arsenic exposure remains a human health risk; however a clear mode of action to understand gene signaling-driven arsenic carcinogenesis is currently lacking. This study chronically exposed human lung epithelial BEAS-2B cells to low-dose arsenic trioxide to elucidate cancer promoting gene signaling networks associated with arsenic-transformed (B-As) cells. Following a 6month exposure, exposed cells were assessed for enhanced cell proliferation, colony formation, invasion ability and in vivo tumor formation compared to control cell lines. Collected mRNA was subjected to whole genome expression microarray profiling followed by in silico Ingenuity Pathway Analysis (IPA) to identify lung carcinogenesis modes of action. B-As cells displayed significant increases in proliferation, colony formation and invasion ability compared to BEAS-2B cells. B-As injections into nude mice resulted in development of primary and secondary metastatic tumors. Arsenic exposure resulted in widespread up-regulation of genes associated with mitochondrial metabolism and increased reactive oxygen species protection suggesting mitochondrial dysfunction. Carcinogenic initiation via reactive oxygen species and epigenetic mechanisms was further supported by altered DNA repair, histone, and ROS-sensitive signaling. NF-κB, MAPK and NCOR1 signaling disrupted PPARα/δ-mediated lipid homeostasis. A 'pro-cancer' gene signaling network identified increased survival, proliferation, inflammation, metabolism, anti-apoptosis and mobility signaling. IPA-ranked signaling networks identified altered p21, EF1α, Akt, MAPK, and NF-κB signaling networks promoting genetic disorder, altered cell cycle, cancer and changes in nucleic acid and energy metabolism. In conclusion, transformed B-As cells with their whole genome expression profile provide an in vitro arsenic model for future lung cancer signaling research and data for chronic arsenic exposure risk assessment.

Genome-wide screening of genes regulated by DNA methylation in colon cancer development

Tumorigenesis is accompanied by changes in the DNA methylation pattern. Our aim was to test a novel approach for identification of transcripts at whole transcript level which are regulated by DNA methylation. Our approach is based on comparison of data obtained from transcriptome profiling of primary human samples and in vitro cell culture models. Epithelial cells were collected by LCM from normal, adenoma, and tumorous colonic samples. Using gene expression analysis, we identified downregulated genes in the tumors compared to normal tissues. In parallel 3000 upregulated genes were determined in HT-29 colon adenocarcinoma cell culture model after DNA demethylation treatment. Of the 2533 transcripts showing reduced expression in the tumorous samples, 154 had increased expression as a result of DNA demethylation treatment. Approximately 2/3 of these genes had decreased expression already in the adenoma samples. Expression of five genes (GCG, NMES-1, LRMP, FAM161B and PTGDR), was validated using RT-PCR. PTGDR showed ambiguous results, therefore it was further studied to verify the extent of DNA methylation and its effect on the protein level. Results confirmed that our approach is suitable for genome-wide screening of genes which are regulated or inactivated by DNA methylation. Activity of these genes possibly interferes with tumor progression, therefore genes identified can be key factors in the formation and in the progression of the disease.