Genome-wide DNA methylation profiling identifies two novel genes in cervical neoplasia

DNA methylation analysis may improve risk stratification in cervical screening. We used a pan-epigenomic approach to identify new methylation markers along the continuum of cervical intraepithelial neoplasia (CIN) to cervical cancer. Physician-collected samples (54 normal, 50 CIN1, 40 CIN2 and 42 CIN3) were randomly selected from women at a single-center colposcopy clinic. Extracted DNA was subjected to Illumina Infinium EPIC array analysis, and methylation was assessed blinded to histopathological and clinical data. CpG sites whose state of methylation correlated with lesion grade were assessed (Spearman correlation), and a weighted methylation score was calculated comparing normal to CIN3. Validation of the top selected genes was performed in an independent cohort (100 normal, 50 CIN1, 50 CIN2, 50 CIN3 and 8 cervical cancers) of new patients, referred for colposcopic examination at three hospitals, using targeted DNA methylation Illumina amplicon sequencing. The relationship between a combined weighted marker score and progression from normal through precancerous lesions and cervical cancer was compared using one-way ANOVA. Our analyses revealed 7,715 CpGs whose methylation level correlated with progression (from normal to CIN1, CIN2 and CIN3), with a significant trend of increased methylation with lesion grade. We shortlisted a bigenic (hyaluronan synthase 1, HAS1 and ATPase phospholipid transporting 10A, ATP10A corresponding to cg03419058 and cg13944175 sites) marker set; r = 0.55, p < 0.0001. Validation of the four most discriminating genes (CA10, DPP10, FMN2 and HAS1) showed a significant correlation between methylation levels and disease progression (p-value < 2.2 × 10⁻¹⁶, adjusted R² = 0.952). Translational research of the identified genes to future clinical applications is warranted.     

Genome-wide DNA methylation profiling of leukocytes identifies CpG methylation signatures of aggressive prostate cancer

Most of screening-detected prostate cancer (PCa) are indolent and not lethal. Biomarkers that can predict aggressive diseases independently of clinical features are needed to improve risk stratification of localized PCa patients and reduce overtreatment. We aimed to identify leukocyte DNA methylation differences between clinically defined aggressive and non-aggressive PCa. We performed whole genome DNA methylation profiling in leukocyte DNA from 287 PCa patients with Gleason Score (GS) 6 and ≥8 using Illumina 450k methylation arrays. We observed a global hypomethylation in GS≥8 patients compared to GS=6 PCa patients; in contrast, the methylation level in core promoter and exon 1 region was significantly higher in GS≥8 patients than GS=6 PCa. We then performed 5-fold cross validated random forest model training on 1,459 differentially methylated CpG Probes (DMPs) with false discovery rate (FDR) <0.01 between GS=6 and GS≥8 groups. The power of the predictive model was further reinforced by ranking the DMPs with Decreased Gini and re-train the model with the top 97 DMPs (Testing AUC=0.920, predict accuracy =0.847). In conclusion, we identified a CpG methylation signature in leukocyte DNA that is associated with aggressive clinical features of PCa at diagnosis.     

Combined RNA/tissue profiling identifies novel Cancer/testis genes

Cancer/Testis (CT) genes are induced in germ cells, repressed in somatic cells, and derepressed in somatic tumors, where these genes can contribute to cancer progression. CT gene identification requires data obtained using standardized protocols and technologies. This is a challenge because data for germ cells, gonads, normal somatic tissues, and a wide range of cancer samples stem from multiple sources and were generated over substantial periods of time. We carried out a GeneChip‐based RNA profiling analysis using our own data for testis and enriched germ cells, data for somatic cancers from the Expression Project for Oncology, and data for normal somatic tissues from the Gene Omnibus Repository. We identified 478 candidate loci that include known CT genes, numerous genes associated with oncogenic processes, and novel candidates that are not referenced in the Cancer/Testis Database (www.cta.lncc.br). We complemented RNA expression data at the protein level for SPESP1, GALNTL5, PDCL2, and C11orf42 using cancer tissue microarrays covering malignant tumors of breast, uterus, thyroid, and kidney, as well as published RNA profiling and immunohistochemical data provided by the Human Protein Atlas (www.proteinatlas.org). We report that combined RNA/tissue profiling identifies novel CT genes that may be of clinical interest as therapeutical targets or biomarkers. Our findings also highlight the challenges of detecting truly germ cell‐specific mRNAs and the proteins they encode in highly heterogenous testicular, somatic, and tumor tissues.     

Genome-wide analysis of DNA methylation identifies novel cancer-related genes in hepatocellular carcinoma

Aberrant DNA methylation has been implicated in the development of hepatocellular carcinoma (HCC). Our aim was to clarify its molecular mechanism and to identify useful biomarkers by screening for DNA methylation in HCC. Methylated CpG island amplification coupled with CpG island microarray (MCAM) analysis was carried out to screen for methylated genes in primary HCC specimens [hepatitis B virus (HBV)-positive, n?=?4; hepatitis C virus (HCV)-positive, n?=?5; HBV/HCV-negative, n?=?7]. Bisulfite pyrosequencing was used to analyze the methylation of selected genes and long interspersed nuclear element (LINE)-1 in HCC tissue (n?=?57) and noncancerous liver tissue (n?=?50) from HCC patients and in HCC cell lines (n?=?10). MCAM analysis identified 332, 342, and 259 genes that were methylated in HBV-positive, HCV-positive, and HBV/HCV-negative HCC tissues, respectively. Among these genes, methylation of KLHL35, PAX5, PENK, and SPDYA was significantly higher in HCC tissue than in noncancerous liver tissue, irrespective of the hepatitis virus status. LINE-1 hypomethylation was also prevalent in HCC and correlated positively with KLHL35 and SPDYA methylation. Receiver operating characteristic curve analysis revealed that methylation of the four genes and LINE-1 strongly discriminated between HCC tissue and noncancerous liver tissue. Our data suggest that aberrant hyper- and hypomethylation may contribute to a common pathogenesis mechanism in HCC. Hypermethylation of KLHL35, PAX, PENK, and SDPYA and hypomethylation of LINE-1 could be useful biomarkers for the detection of HCC.     

Suppression subtractive hybridization and expression profiling identifies a unique set of genes overexpressed in non-small-cell lung cancer

Expression array data for >3000 individual clones from two suppression subtractive hybridization libraries revealed 147 genes overexpressed in non-small-cell lung cancer (NSCLC) cell lines. Of these 147 genes, 30 genes have previously unknown cancer association and 65 genes have been associated with cancers other than NSCLC. The identification of 52 genes previously associated with NSCLC by different methodologies supports the validity of the strategy used here. Of the 147 genes, 19 have no prior named Unigene cluster designation, and are designated herein as L1 to L19. Quantitative real-time PCR and cancer profiling arrays were used as independent validation tools to confirm tumor overexpression for five of the 'L' genes in tumor cell lines and patient samples from NSCLC and other cancers. Follow-up studies for candidate NSCLC-associated genes can be useful in providing valuable insight into the etiology of lung cancer as well as providing potentially interesting diagnostic or therapeutic targets for further investigation.     

Genome-wide DNA methylation profiling reveals novel epigenetically regulated genes and non-coding RNAs in human testicular cancer

Background:

Testicular germ cell tumour (TGCT) is the most common malignant tumour in young males. Although aberrant DNA methylation is implicated in the pathophysiology of many cancers, only a limited number of genes are known to be epigenetically changed in TGCT. This report documents the genome-wide analysis of differential methylation in an in vitro model culture system. Interesting genes were validated in TGCT patient samples.

Methods:

In this study, we used methylated DNA immunoprecipitation (MeDIP) and whole-genome tiling arrays to identify differentially methylated regions (DMRs).

Results:

We identified 35 208 DMRs. However, only a small number of DMRs mapped to promoters. A genome-wide analysis of gene expression revealed a group of differentially expressed genes that were regulated by DNA methylation. We identified several candidate genes, including APOLD1, PCDH10 and RGAG1, which were dysregulated in TGCT patient samples. Surprisingly, APOLD1 had previously been mapped to the TGCT susceptibility locus at 12p13.1, suggesting that it may be important in TGCT pathogenesis. We also observed aberrant methylation in the loci of some non-coding RNAs (ncRNAs). One of the ncRNAs, hsa-mir-199a, was downregulated in TGCT patient samples, and also in our in vitro model culture system.

Conclusion:

This report is the first application of MeDIP-chip for identifying epigenetically regulated genes and ncRNAs in TGCT. We also demonstrated the function of intergenic and intronic DMRs in the regulation of ncRNAs.     

Molecular profiling of low grade serous ovarian tumours identifies novel candidate driver genes

Low grade serous ovarian tumours are a rare and under-characterised histological subtype of epithelial ovarian tumours, with little known of the molecular drivers and facilitators of tumorigenesis beyond classic oncogenic RAS/RAF mutations. With a move towards targeted therapies due to the chemoresistant nature of this subtype, it is pertinent to more fully characterise the genetic events driving this tumour type, some of which may influence response to therapy and/or development of drug resistance. We performed genome-wide high-resolution genomic copy number analysis (Affymetrix SNP6.0) and mutation hotspot screening (KRAS, BRAF, NRAS, HRAS, ERBB2 and TP53) to compare a large cohort of ovarian serous borderline tumours (SBTs, n = 57) with low grade serous carcinomas (LGSCs, n = 19). Whole exome sequencing was performed for 13 SBTs, nine LGSCs and one mixed low/high grade carcinoma. Copy number aberrations were detected in 61% (35/57) of SBTs, compared to 100% (19/19) of LGSCs. Oncogenic RAS/RAF/ERBB2 mutations were detected in 82.5% (47/57) of SBTs compared to 63% (12/19) of LGSCs, with NRAS mutations detected only in LGSC. Some copy number aberrations appeared to be enriched in LGSC, most significantly loss of 9p and homozygous deletions of the CDKN2A/2B locus. Exome sequencing identified BRAF, KRAS, NRAS, USP9X and EIF1AX as the most frequently mutated genes. We have identified markers of progression from borderline to LGSC and novel drivers of LGSC. USP9X and EIF1AX have both been linked to regulation of mTOR, suggesting that mTOR inhibitors may be a key companion treatment for targeted therapy trials of MEK and RAF inhibitors.     

Expression profiling identifies genes involved in neoplastic transformation of serous ovarian cancer

Background  

The malignant potential of serous ovarian tumors, the most common ovarian tumor subtype, varies from benign to low malignant potential (LMP) tumors to frankly invasive cancers. Given the uncertainty about the relationship between these different forms, we compared their patterns of gene expression.     

Differential methylation hybridization profiling identifies involvement of STAT1-mediated pathways in breast cancer

Many cancer-related genes are regulated by an epigenetic mechanism through modification of the methylation status of CpG sites at the promoter. This study was carried out at a genome-wide scale to mine genes in which the methylation of CpG sites is altered in breast cancer tissues. Differential methylation hybridization analysis was conducted using a chromosomal DNA mixture of ten normal and cancer tissue sets. A CpG microarray harboring 237,220 CpG sites of the whole genome was interrogated and the resulting methylation level differences, as well as the RNA expression differences, between the normal and cancer sets for selected genes were verified in breast cell lines by methylation-specific PCR and real-time PCR analyses. As a result, we identified and verified novel genes that were hypermethylated in breast cancer, such as NRN1, CA5B and RPIA. Pathway analysis of the genes with altered methylation patterns identified the involvement of a differentiation-related network of genes whose activity may be heavily regulated by STAT1 in breast tumorigenesis. Our results suggest that epigenetic dysregulation of cellular processes relevant to STAT1-dependent cellular differentiation may be intimately involved in breast carcinogenesis. These findings lend credence to the possibility of using tumor-specific alterations in methylation patterns as biomarkers in estimating prognosis and assessing treatment options for breast cancer.     

Phenotypic profiling identifies novel anticancer drugs

Image analysis of vasculature in a tumor-derived 3D matrix shows high predictive value in discovering angiogenesis inhibitors.     

Global methylation profiling to identify epigenetic signature of gallbladder cancer and gallstone disease

Tumor Biology - Promoter methylation in various tumor suppressor genes is reported to influence gallbladder carcinogenesis. Here, we aimed to identify methylation status in gallbladder cancer (GBC)...     

MIRA-assisted microarray analysis, a new technology for the determination of DNA methylation patterns, identifies frequent methylation of homeodomain-containing genes in lung cancer cells

We present a straightforward and comprehensive approach for DNA methylation analysis in mammalian genomes. The methylated-CpG island recovery assay (MIRA), which is based on the high affinity of the MBD2/MBD3L1 complex for methylated DNA, has been used to detect cell type-dependent differences in DNA methylation on a microarray platform. The procedure has been verified and applied to identify a series of novel candidate lung tumor suppressor genes and potential DNA methylation markers that contain methylated CpG islands. One gene of particular interest was DLEC1, located at a commonly deleted area on chromosome 3p22-p21.3, which was frequently methylated in primary lung cancers and melanomas. Among the identified methylated genes, homeodomain-containing genes were unusually frequent (11 of the top 50 hits) and were targeted on different chromosomes. These genes included LHX2, LHX4, PAX7, HOXB13, LBX1, SIX2, HOXD3, DLX1, HOXD1, ONECUT2, and PAX9. The data show that MIRA-assisted microarray analysis has a low false-positive rate and has the capacity to catalogue methylated CpG islands on a genome-wide basis. The results support the hypothesis that cancer-associated DNA methylation events do not occur randomly throughout the genome but at least some are targeted by specific mechanisms.