Identification of novel high-frequency DNA methylation changes in breast cancer

Recent data have revealed that epigenetic alterations, including DNA methylation and chromatin structure changes, are among the earliest molecular abnormalities to occur during tumorigenesis. The inherent thermodynamic stability of cytosine methylation and the apparent high specificity of the alterations for disease may accelerate the development of powerful molecular diagnostics for cancer. We report a genome-wide analysis of DNA methylation alterations in breast cancer. The approach efficiently identified a large collection of novel differentially DNA methylated loci (approximately 200), a subset of which was independently validated across a panel of over 230 clinical samples. The differential cytosine methylation events were independent of patient age, tumor stage, estrogen receptor status or family history of breast cancer. The power of the global approach for discovery is underscored by the identification of a single differentially methylated locus, associated with the GHSR gene, capable of distinguishing infiltrating ductal breast carcinoma from normal and benign breast tissues with a sensitivity and specificity of 90% and 96%, respectively. Notably, the frequency of these molecular abnormalities in breast tumors substantially exceeds the frequency of any other single genetic or epigenetic change reported to date. The discovery of over 50 novel DNA methylation-based biomarkers of breast cancer may provide new routes for development of DNA methylation-based diagnostics and prognostics, as well as reveal epigenetically regulated mechanism involved in breast tumorigenesis.     

Methylation profiling identified novel differentially methylated markers including OPCML and FLRT2 in prostate cancer

To develop new methods to distinguish indolent from aggressive prostate cancers (PCa), we utilized comprehensive high-throughput array-based relative methylation (CHARM) assay to identify differentially methylated regions (DMRs) throughout the genome, including both CpG island (CGI) and non-CGI regions in PCa patients based on Gleason grade. Initially, 26 samples, including 8 each of low [Gleason score (GS) 6] and high (GS ≥7) grade PCa samples and 10 matched normal prostate tissues, were analyzed as a discovery cohort. We identified 3,567 DMRs between normal and cancer tissues, and 913 DMRs distinguishing low from high-grade cancers. Most of these DMRs were located at CGI shores. The top 5 candidate DMRs from the low vs. high Gleason comparison, including OPCML, ELAVL2, EXT1, IRX5, and FLRT2, were validated by pyrosequencing using the discovery cohort. OPCML and FLRT2 were further validated in an independent cohort consisting of 20 low-Gleason and 33 high-Gleason tissues. We then compared patients with biochemical recurrence (n=70) vs. those without (n=86) in a third cohort, and they showed no difference in methylation at these DMR loci. When GS 3+4 cases and GS 4+3 cases were compared, OPCML-DMR methylation showed a trend of lower methylation in the recurrence group (n=30) than in the no-recurrence (n=52) group. We conclude that whole-genome methylation profiling with CHARM revealed distinct patterns of differential DNA methylation between normal prostate and PCa tissues, as well as between different risk groups of PCa as defined by Gleason scores. A panel of selected DMRs may serve as novel surrogate biomarkers for Gleason score in PCa.     

Novel markers of gene methylation and expression in breast cancer

An optimized methylation-sensitive restriction fingerprinting technique was used to search for differentially methylated CpG islands in the tumor genome and detected seven genes subject to abnormal epigenetic regulation in breast cancer: SEMA6B, BIN1, VCPIP1, LAMC3, KCNH2, CACNG4, and PSMF1. For each gene, the rate of promoter methylation and changes in expression were estimated in tumor and morphologically intact paired specimens of breast tissue (N = 100). Significant methylation rates of 38, 18, and 8% were found for SEMA6B, BIN1, and LAMC3, respectively. The genes were not methylated in morphologically intact breast tissue. The expression of SEMA6B, BIN1, VCPIP1, LAMC3, KCNH2, CACNG4, and PSMF1 was decreased in 44–94% of tumor specimens by the real-time RT-PCR assay. The most profound changes in SEMA6B and LAMC3 suggest that these genes can be included in biomarker panels for breast cancer diagnosis. Fine methylation mapping of the most frequently methylated CpG islands (SEMA6B, BIN1, and LAMC3) provides a fundamental basis for developing efficient methylation tests for these genes.     

Novel methylation and expression markers associated with breast cancer

We have developed a modification of methylation sensitive arbitrarily primed PCR, one of the methods of differentially methylated CpG islands in cancer cells genomes screening. Seven genes undergoing abnormal epigenetic regulation in breast cancer, SEMA6B, BIN1, VCPIP1, LAMC3, KCNH2, CACNG4 and PSMF1, have been identified by this method. Methylation and loss of expression frequencies were evaluated for each of the identified genes on 100 paired (cancer/morphologically intact control) breast tissue samples. Significant frequencies of abnormal methylation were detected for SEMA6B, BIN1, and LAMC3 (38%, 18%, and 8% correspondingly). Methylation of the above genes was not characteristic for morphologically intact breast tissues. Downregulation of SEMA6B, BIN1, VCPIP1, LAMC3, KCNH2, CACNG4 and PSMF1 in breast cancer was as frequent as 44-94% by real-time PCR expression assay. The most pronounced functional alterations were demonstrated for SEMA6B and LAMC3 genes, which allows recommending their inclusion into the panels of carcinogenesis diagnostic panels. Fine methylation mapping was performed for the genes most frequently methylated in breast cancer (SEMA6B, BIN1, LAMC3), providing a fundamental basis for the development of effective methylation tests for these genes.     

Detection of novel amplicons in prostate cancer by comprehensive genomic profiling of prostate cancer cell lines using oligonucleotide-based arrayCGH

BACKGROUND: The purpose of this study was to prove the feasibility of a longmer oligonucleotide microarray platform to profile gene copy number alterations in prostate cancer cell lines and to quickly indicate novel candidate genes, which may play a role in carcinogenesis. METHODS/RESULTS AND FINDINGS: Genome-wide screening for regions of genetic gains and losses on nine prostate cancer cell lines (PC3, DU145, LNCaP, CWR22, and derived sublines) was carried out using comparative genomic hybridization on a 35,000 feature oligonucleotide microarray (arrayCGH). Compared to conventional chromosomal CGH, more deletions and small regions of gains, particularly in pericentromeric regions and regions next to the telomeres, were detected. As validation of the high-resolution of arrayCGH we further analyzed a small amplicon of 1.7 MB at 9p13.3, which was found in CWR22 and CWR22-Rv1. Increased copy number was confirmed by fluorescence in situ hybridization using the BAC clone RP11-165H19 from the amplified region comprising the two genes interleukin 11 receptor alpha (IL11-RA) and dynactin 3 (DCTN3). Using quantitative real time PCR (qPCR) we could demonstrate that IL11-RA is the gene with the highest copy number gain in the cell lines compared to DCTN3 suggesting IL11-RA to be the amplification target. Screening of 20 primary prostate carcinomas by qPCR revealed an IL11-RA copy number gain in 75% of the tumors analyzed. Gain of DCTN3 was only found in two cases together with a gain of IL11-RA. CONCLUSIONS/SIGNIFICANCE: ArrayCGH using longmer oligonucleotide microarrays is feasible for high-resolution analysis of chomosomal imbalances. Characterization of a small gained region at 9p13.3 in prostate cancer cell lines and primary prostate cancer samples by fluorescence in situ hybridization and quantitative PCR has revealed interleukin 11 receptor alpha gene as a candidate target of amplification with an amplification frequency of 75% in prostate carcinomas. Frequent amplification of IL11-RA in prostate cancer is a potential mechanism of IL11-RA overexpression in this tumor type.     

DNA methylation profiling distinguishes three clusters of breast cancer cell lines

Methylation change plays an important role in many cellular systems, including cancer development. During recent years, genome-wide or large-scale methylation data has become available thanks to rapid advances in high-throughput biotechnologies. So far, researchers have always used gene expression profiling to study disease subtypes and related therapies. In this study, we investigated methylation profiles in 30 breast cancer cell lines using methylation data generated by microarray technologies. Strong variation of the number of methylation peaks was found among these 30 cell lines; however, more peaks were found in the upstream regions than in downstream regions of genes. We further grouped the methylation profiles of these cell lines into three consensus clusters. Finally, we performed an integrative analysis of breast cancer cell lines using both methylation and gene-expression profiling data. There was no significant correlation between methylation-profiling subtypes and gene-expression profiling subtypes, suggesting the complex nature of methylation in the regulation of gene expression. However, we found basal B cell lines appeared exclusively in two methylation clusters. Although these results are preliminary, this study suggests that methylation profiling might be promising in disease subtype classification and the development of therapeutic strategies.     

Identification of vascular breast tumor markers by laser capture microdissection and label-free LC-MS

Blood vessels in tumors frequently show abnormal characteristics, such as tortuous morphology or leakiness, but very little is known about protein expression in tumor vessels. In this study, we have used laser capture microdissection (LCM) to isolate microvessels from clinical samples of invasive ductal carcinoma (IDC), the most common form of malignant breast cancer, and from patient-matched adjacent nonmalignant tissue. This approach eliminates many of the problems associated with the heterogeneity of clinical tumor tissues by controlling for differences in protein expression between both individual patients and different cell types. Proteins from the microvessels were trypsinized and the resulting peptides were quantified by a label-free nanoLC-MS method. A total of 86 proteins were identified that are overexpressed in tumor vessels relative to vessels isolated from the adjacent nonmalignant tissue. These proteins include well-known breast tumor markers such as Periostin and Tenascin C but also proteins with lesser-known or emerging roles in breast cancer and tumor angiogenesis (i.e., Serpin H1, Clic-1, and Transgelin 2). We also identified 40 proteins that were relatively under-expressed in IDC tumor vessels, including several components of the basement membrane whose lower expression could be responsible for weakening tumor vessels. Lastly, we show that a subset of 29 proteins, derived from our list of differentially expressed proteins, is able to predict survival in three publicly available clinical breast cancer microarray data sets, which suggests that this subset of proteins likely plays a functional role in cancer progression and outcome.     

Circulating tumor cells from patients with advanced prostate and breast cancer display both epithelial and mesenchymal markers

During cancer progression, malignant cells undergo epithelial-mesenchymal transitions (EMT) and mesenchymal-epithelial transitions (MET) as part of a broad invasion and metastasis program. We previously observed MET events among lung metastases in a preclinical model of prostate adenocarcinoma that suggested a relationship between epithelial plasticity and metastatic spread. We thus sought to translate these findings into clinical evidence by examining the existence of EMT in circulating tumor cells (CTC) from patients with progressive metastatic solid tumors, with a focus on men with castration-resistant prostate cancer (CRPC) and women with metastatic breast cancer. We showed that the majority (> 80%) of these CTCs in patients with metastatic CRPC coexpress epithelial proteins such as epithelial cell adhesion molecule (EpCAM), cytokeratins (CK), and E-cadherin, with mesenchymal proteins including vimentin, N-cadherin and O-cadherin, and the stem cell marker CD133. Equally, we found that more than 75% of CTCs from women with metastatic breast cancer coexpress CK, vimentin, and N-cadherin. The existence and high frequency of these CTCs coexpressing epithelial, mesenchymal, and stem cell markers in patients with progressive metastases has important implications for the application and interpretation of approved methods to detect CTCs.     

Abnormal methylation of several tumor suppressor genes in sporadic breast cancer

Multiplex methylation-sensitive PCR was employed in studying the methylation of CpG islands in the RB1, p16/CDKN2A, p15/CDKN2B, p14/ARF, CDH1, MGMT, HIC1, and N33 promoter regions in breast carcinoma (105 tumors). Methylation was often observed for the two major suppressor genes involved in cell-cycle control through the Cdk-Rb-E2F signaling pathway, RB1 (18/105, 17%) and p16 (59/105, 56%); both genes were methylated in 13 tumors. Methylation involved p15 in two (2%) tumors; CDH1, in 83 (79%) tumors; MGMT, in eight (8%) tumors, and N33, in nine (9%) tumors. The p14 promoter was not methylated in the tumors examined.     

Identification of novel epigenetically modified genes in human melanoma via promoter methylation gene profiling

The inactivation of tumor-related genes through the aberrant methylation of promoter CpG islands is thought to contribute to tumor initiation and progression. We therefore investigated promoter methylation events involved in cutaneous melanoma by screening 30 genes of interest for evidence of promoter hypermethylation, examining 20 melanoma cell lines and 40 freshly procured melanoma samples. Utilizing quantitative methylation-specific PCR, we identified five genes (SOCS1, SOCS2, RAR-beta 2, TNFSF10C, and TNFSF10D) with hypermethylation frequencies ranging from 50% to 80% in melanoma cell lines as well as freshly procured tissue samples. Eighteen genes (LOX, RASSF1A, WFDC1, TM, APC, TFPI2, TNFSF10A, CDKN2A, MGMT, TIMP3, ASC, TPM1, IRF8, CIITA-PIV, CDH1, SYK, HOXB13, and DAPK1) were methylated at lower frequencies (2-30%). Two genes (CDKN1B and PTEN), previously reported as methylated in melanoma, and five other genes (RECK, IRF7, PAWR, TNFSF10B, and Rb) were not methylated in the samples screened here. Daughter melanoma cell lines showed identical methylation patterns when compared with original samples from which they were derived, as did synchronous metastatic lesions from the same patient. We identified four genes (TNFSF10C, TNFSF10D, LOX, and TPM1) that have never before been identified as hypermethylated in melanoma, with an overall methylation frequency of 60, 80, 50, and 10%, respectively, hypothesizing that these genes may play an important role in melanoma progression.     

DNA methylation in prostate cancer

Prostate cancer is the most common malignancy and the second leading cause of cancer death among men in the United States. There are three well-established risk factors for prostate cancer: age, race and family history. The molecular bases for these risk factors are unclear; however, they may be influenced by epigenetic events. Epigenetic events covalently modify chromatin and alter gene expression. Methylation of cytosine residues within CpG islands on gene promoters is a primary epigenetic event that acts to suppress gene expression. In tumorigenesis, the normal functioning of the epigenetic-regulatory system is disrupted leading to inappropriate CpG island hypermethylation and aberrant expression of a battery of genes involved in critical cellular processes. Cancer-dependent epigenetic regulation of genes involved in DNA damage repair, hormone response, cell cycle control and tumor-cell adhesion/metastasis can contribute significantly to tumor initiation, progression and metastasis and, thereby, increase prostate cancer susceptibility and risk. In this review, we will discuss current research on genes that are hypermethylated in human prostate cancer. We will also discuss the potential involvement of DNA methylation in age-related, race-related and hereditary prostate cancer, and the potential use of hypermethylated genes as biomarkers to detect prostate cancer and assess its risk.     

DNA methylation changes correlate with Gleason score and tumor stage in prostate cancer

DNA methylation, a widely used epigenetic mark, has been associated with many tumors. However, few studies have addressed the role of cell-free plasma DNA methylation in discriminating aggressive prostate cancer (PCa) from indolent cases. We conducted a case series and a case-control study among histologically confirmed stage II/III cases and matched controls recruited at Columbia University Medical Center. The aim of this study was to investigate whether plasma DNA methylation levels are appropriate surrogate biomarker of PCa tumor tissue levels and whether these markers are associated with worse clinicopathological tumor characteristics, which correlate with poorer prognosis. Quantitative pyrosequencing was used to detect methylation levels of p16 (CDKN4A), APC, GSTP1, and LINE-1 in 24 pairs of prostate tumor and adjacent tissues, as well as 27 plasma samples of PCa patients and 24 of controls. DNA methylation levels were significantly higher in tumor tissue than in adjacent nontumor tissue for p16 (CDKN4A), GSTP1, and APC; GSTP1 had a higher average percentage methylation in tumor tissue (38.9%) compared with p16 (CDKN4A) (5.9%) and APC (14.5%). GSTP1, p16 (CDKN4A), and APC methylation in tumor tissue was statistically significantly higher for cases with Gleason score ≥7 compared with those with Gleason score <7 [49.0% vs. 21.9% (p=0.01), 6.6% vs. 4.5% (p=0.04), and 19.1% vs. 7.4% (p=0.02), respectively]. Plasma LINE-1 methylation levels were higher in those with higher Gleason (67.6%) than in those with Gleason's below 7 (64.6%, p=0.03). Significant plasma-tissue correlations were observed for GSTP1 and LINE-1 methylation. These data, although preliminary, suggest that aberrant methylation may be a useful marker to identify PCa patients with clinically aggressive disease.     

DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer

Germline pathogenic mutations in BRCA1 increase risk of developing breast cancer. Screening for mutations in BRCA1 frequently identifies sequence variants of unknown pathogenicity and recent work has aimed to develop methods for determining pathogenicity. We previously observed that tumor DNA methylation can differentiate BRCA1-mutated from BRCA1-wild type tumors. We hypothesized that we could predict pathogenicity of variants based on DNA methylation profiles of tumors that had arisen in carriers of unclassified variants. We selected 150 FFPE breast tumor DNA samples [47 BRCA1 pathogenic mutation carriers, 65 BRCAx (BRCA1-wild type), 38 BRCA1 test variants] and analyzed a subset (n=54) using the Illumina 450K methylation platform, using the remaining samples for bisulphite pyrosequencing validation. Three validated markers (BACH2, C8orf31, and LOC654342) were combined with sequence bioinformatics in a model to predict pathogenicity of 27 variants (independent test set).  Predictions were compared with standard multifactorial likelihood analysis. Prediction was consistent for c.5194-12G>A (IVS 19-12 G>A) (P>0.99); 13 variants were considered not pathogenic or likely not pathogenic using both approaches. We conclude that tumor DNA methylation data alone has potential to be used in prediction of BRCA1 variant pathogenicity but is not independent of estrogen receptor status and grade, which are used in current multifactorial models to predict pathogenicity.     

Identification of novel variants of metadherin in breast cancer

Metadherin (MTDH, also known as AEG-1, and Lyric) has been demonstrated to play a potential role in several significant aspects of tumor progression. It has been reported that overexpression of MTDH is associated with progression of disease and poorer prognosis in breast cancer. However, there are no studies to date assessing variants of the MTDH gene and their potential relationship with breast cancer susceptibility. Thus, we investigated all variants of the MTDH gene and explored the association of the variants with breast cancer development. Our cohort consisted of full-length gene sequencing of 108 breast cancer cases and 100 healthy controls; variants were detected in 11 breast cancer cases and 13 controls. Among the variants detected, 9 novel variants were discovered and 2 were found to be associated with the susceptibility of breast cancer. However, additional studies need to be conducted in larger sample sizes to validate these findings and to further investigate whether these variants are prognostic in breast cancer patients.