Targeting bivalency de-represses Indian Hedgehog and inhibits self-renewal of colorectal cancer-initiating cells.

In embryonic stem cells, promoters of key lineage-specific differentiation genes are found in a bivalent state, having both activating H3K4me3 and repressive H3K27me3 histone marks, making them poised for transcription upon loss of H3K27me3. Whether cancer-initiating cells (C-ICs) have similar epigenetic mechanisms that prevent lineage commitment is unknown. Here we show that colorectal C-ICs (CC-ICs) are maintained in a stem-like state through a bivalent epigenetic mechanism. Disruption of the bivalent state through inhibition of the H3K27 methyltransferase EZH2, resulted in decreased self-renewal of patient-derived C-ICs. Epigenomic analyses revealed that the promoter of Indian Hedgehog (IHH), a canonical driver of normal colonocyte differentiation, exists in a bivalent chromatin state. Inhibition of EZH2 resulted in de-repression of IHH, decreased self-renewal, and increased sensitivity to chemotherapy in vivo. Our results reveal an epigenetic block to differentiation in CC-ICs and demonstrate the potential for epigenetic differentiation therapy of a solid tumour through EZH2 inhibition.

Genes Predisposed to DNA Hypermethylation during Acquired Resistance to Chemotherapy Are Identified in Ovarian Tumors by Bivalent Chromatin Domains at Initial Diagnosis.

Bivalent chromatin domains containing both active H3K4me3 and repressive H3K27me3 histone marks define gene sets poised for expression or silencing in differentiating embryonic stem (ES) cells. In cancer cells, aberrantly poised genes may facilitate changes in transcriptional states after exposure to anticancer drugs. In this study, we used ChIP-seq to characterize genome-wide positioning of H3K4me3- and H3K27me3-associated chromatin in primary high-grade serous ovarian carcinomas and in normal ovarian surface and fallopian tube tissue. Gene sets with proximal bivalent marks defined in this manner were evaluated subsequently as signatures of systematic change in DNA methylation and gene expression, comparing pairs of tissue samples taken from patients at primary presentation and relapse following chemotherapy. We found that gene sets harboring bivalent chromatin domains at their promoters in tumor tissue, but not normal epithelia, overlapped with Polycomb-repressive complex target genes as well as transcriptionally silenced genes in normal ovarian and tubal stem cells. The bivalently marked genes we identified in tumors before chemotherapy displayed increased promoter CpG methylation and reduced gene expression at relapse after chemotherapy of ovarian cancer. Overall, our results support the hypothesis that preexisting histone modifications at genes in a poised chromatin state may lead to epigenetic silencing during acquired drug resistance.Significance: These results suggest epigenetic targets for intervention to prevent the emergence of cancer drug resistance. Cancer Res; 78(6); 1383-91. ©2018 AACR.

Integrated (epi)-Genomic Analyses Identify Subgroup-Specific Therapeutic Targets in CNS Rhabdoid Tumors.

We recently reported that atypical teratoid rhabdoid tumors (ATRTs) comprise at least two transcriptional subtypes with different clinical outcomes; however, the mechanisms underlying therapeutic heterogeneity remained unclear. In this study, we analyzed 191 primary ATRTs and 10 ATRT cell lines to define the genomic and epigenomic landscape of ATRTs and identify subgroup-specific therapeutic targets. We found ATRTs segregated into three epigenetic subgroups with distinct genomic profiles, SMARCB1 genotypes, and chromatin landscape that correlated with differential cellular responses to a panel of signaling and epigenetic inhibitors. Significantly, we discovered that differential methylation of a PDGFRB-associated enhancer confers specific sensitivity of group 2 ATRT cells to dasatinib and nilotinib, and suggest that these are promising therapies for this highly lethal ATRT subtype.

A Critical Evaluation of the PAXgene Tissue Fixation System: Morphology, Immunohistochemistry, Molecular Biology, and Proteomics.

OBJECTIVES: To evaluate the PAXgene tissue fixation system. METHODS: Clinical biospecimens (n = 46) were divided into PAXgene-fixed paraffin-embedded (PFPE), formalin-fixed paraffin-embedded (FFPE), and fresh-frozen (FF) blocks. PFPE and FFPE sections were compared for histology (H&E staining) and immunohistochemistry (14 antibodies) using tissue microarrays. PFPE, FFPE, and FF samples were compared in terms of RNA quality (RNA integrity number, polymerase chain reaction [PCR] amplicon length, and quantitative reverse transcription PCR), DNA quality (gel electrophoresis and methylation profiling) and protein quality (liquid chromatography-mass spectrometry [LC-MS/MS]). RESULTS: PFPE protocol optimization was required in most cases and is described. RNA extracted from PFPE sections was considerably less degraded than that from FFPE sections but more degraded than that from FF blocks. Genomic-length DNA was extracted from PFPE and FF biospecimens, and methylation profiling showed PFPE and FF biospecimens to be almost indistinguishable. Only degraded DNA was extracted from FFPE biospecimens. PFPE sections yielded peptides that were slightly less amenable to LC-MS/MS analysis than FFPE sections, but FF gave slightly better results. CONCLUSIONS: While it cannot be envisaged that PAXgene will replace formalin in a routine clinical setting, for specific projects or immunodiagnostics involving biospecimens destined for immunohistochemical or histologic staining and DNA or RNA analyses, PAXgene is a viable option.

Aberrant DNA methylation at genes associated with a stem cell-like phenotype in cholangiocarcinoma tumors.

Genetic abnormalities of cholangiocarcinoma have been widely studied; however, epigenomic changes related to cholangiocarcinogenesis have been less well characterized. We have profiled the DNA methylomes of 28 primary cholangiocarcinoma and six matched adjacent normal tissues using Infinium's HumanMethylation27 BeadChips with the aim of identifying gene sets aberrantly and epigenetically regulated in this tumor type. Using a linear model for microarray data, we identified 1610 differentially methylated autosomal CpG sites, with 809 hypermethylated (representing 603 genes) and 801 hypomethylated (representing 712 genes) in cholangiocarcinoma versus adjacent normal tissues (false-discovery rate ≤ 0.05). Gene ontology and gene set enrichment analyses identified gene sets significantly associated with hypermethylation at linked CpG sites in cholangiocarcinoma including homeobox genes and target genes of PRC2, EED, SUZ12, and histone H3 trimethylation at lysine 27. We confirmed frequent hypermethylation at the homeobox genes HOXA9 and HOXD9 by bisulfite pyrosequencing in a larger cohort of cholangiocarcinoma (n = 102). Our findings indicate a key role for hypermethylation of multiple CpG sites at genes associated with a stem cell-like phenotype as a common molecular aberration in cholangiocarcinoma. These data have implications for cholangiocarcinogenesis, as well as possible novel treatment options using histone methyltransferase inhibitors.

Promoter CpG island methylation of genes in key cancer pathways associates with clinical outcome in high-grade serous ovarian cancer.

PURPOSE: We aimed to identify DNA methylation biomarkers of progression-free survival (PFS) to platinum-based chemotherapy in high-grade serous ovarian cancer (HGSOC) within biologically relevant ovarian cancer-associated pathways. EXPERIMENTAL DESIGN: Association with PFS of CpG island (CGI) promoter DNA methylation at genes in the pathways Akt/mTOR, p53, redox, and homologous recombination DNA repair was sought with PFS as the primary objective in a prospectively collected ovarian cancer cohort (n = 150). Significant loci were validated for associations between PFS, methylation, and gene expression in an independent The Cancer Genome Atlas (TCGA) data set of HGSOC (n = 311). RESULTS: DNA methylation at 29 CGI loci linked to 28 genes was significantly associated with PFS, independent from conventional clinical prognostic factors (adjusted P < 0.05). Of 17 out of the 28 genes represented in the TCGA data set, methylation of VEGFB, VEGFA, HDAC11, FANCA, E2F1, GPX4, PRDX2, RAD54L, and RECQL4 was prognostic in this independent patient cohort (one-sided P < 0.05, false discovery rate < 10%). A multivariate Cox model was constructed, with clinical parameters (age, stage, grade, and histologic type) and significant loci. The final model included NKD1, VEGFB, and PRDX2 as the three best predictors of PFS (P = 6.62 × 10(-6), permutation test P < 0.05). Focussing only on known VEGFs in the TCGA cohort showed that methylation at promoters of VEGFA, VEGFB, and VEGFC was significantly associated with PFS. CONCLUSIONS: A three loci model of DNA methylation could identify two distinct prognostic groups of patients with ovarian cancer (PFS: HR = 2.29, P = 3.34 × 10(-5); overall survival: HR = 1.87, P = 0.007) and patients more likely to have poor response to chemotherapy (OR = 3.45, P = 0.012).

The DNA methylomes of serous borderline tumors reveal subgroups with malignant- or benign-like profiles.

Serous borderline tumors (SBOTs) are a challenging group of ovarian tumors positioned between benign and malignant disease. We have profiled the DNA methylomes of 12 low-grade serous carcinomas (LGSCs), 19 SBOTs, and 16 benign serous tumors (BSTs) across 27,578 CpG sites to further characterize the epigenomic relationship between these subtypes of ovarian tumors. Unsupervised hierarchical clustering of DNA methylation levels showed that LGSCs differ distinctly from BSTs, but not from SBOTs. Gene ontology analysis of genes showing differential methylation at linked CpG sites between LGSCs and BSTs revealed significant enrichment of gene groups associated with cell adhesion, cell-cell signaling, and the extracellular region, consistent with a more invasive phenotype of LGSCs compared with BSTs. Consensus clustering highlighted differences between SBOT methylomes and returned subgroups with malignant- or benign-like methylation profiles. Furthermore, a two-loci DNA methylation signature can distinguish between these SBOT subgroups with benign- and malignant-like methylation characteristics. Our findings indicate striking similarities between SBOT and LGSC methylomes, supporting a common origin and the view that LGSC may arise from SBOT. A subgroup of SBOTs can be classified into tumors with a benign- or a malignant-like methylation profile that may help in identifying tumors more likely to progress into LGSCs.

Systematic CpG islands methylation profiling of genes in the wnt pathway in epithelial ovarian cancer identifies biomarkers of progression-free survival.

PURPOSE: Wnt pathways control key biological processes that potentially impact on tumor progression and patient survival. We aimed to evaluate DNA methylation at promoter CpG islands (CGI) of Wnt pathway genes in ovarian tumors at presentation and identify biomarkers of patient progression-free survival (PFS). EXPERIMENTAL DESIGN: Epithelial ovarian tumors (screening study n = 120, validation study n = 61), prospectively collected through a cohort study, were analyzed by differential methylation hybridization at 302 loci spanning 189 promoter CGIs at 137 genes in Wnt pathways. The association of methylation and PFS was examined by Cox proportional hazards model. RESULTS: DNA methylation is associated with PFS at 20 of 302 loci (P < 0.05, n = 111), with 5 loci significant at false discovery rate (FDR) less than 10%. A total of 11 of 20 loci retain significance in an independent validation cohort (n = 48, P ≤ 0.05, FDR ≤ 10%), and 7 of these loci, at FZD4, DVL1, NFATC3, ROCK1, LRP5, AXIN1, and NKD1 genes, are independent from clinical parameters (adjusted P < 0.05). Increased methylation at these loci associates with increased hazard of disease progression. A multivariate Cox model incorporates only NKD1 and DVL1, identifying two groups differing in PFS [HR = 2.09; 95% CI (1.39-3.15); permutation test P < 0.005]. Methylation at DVL1 and NFATC3 show significant association with response. Consistent with their epigenetic regulation, reduced expression of FZD4, DVL1, and ROCK1 is an indicator of early-disease relapse in an independent ovarian tumor cohort (n = 311, adjusted P < 0.05). CONCLUSION: The data highlight the importance of epigenetic regulation of multiple promoter CGIs of Wnt pathway genes in ovarian cancer and identify methylation at NKD1 and DVL1 as independent predictors of PFS.

Therapeutic modulation of epigenetic drivers of drug resistance in ovarian cancer.

Epigenetic changes in tumours are associated not only with cancer development and progression, but also with resistance to chemotherapy. Aberrant DNA methylation at CpG islands and associated epigenetic silencing are observed during the acquisition of drug resistance. However, it remains unclear whether all of the observed changes are drivers of drug resistance, causally associated with response of tumours to chemotherapy, or are passenger events representing chance DNA methylation changes. Systematic approaches that link DNA methylation and expression with chemosensitivity will be required to identify key drivers. Such drivers will be important prognostic or predicitive biomarkers, both to existing chemotherapies, but also to epigenetic therapies used to modulate drug resistance.

Methylation Linear Discriminant Analysis (MLDA) for identifying differentially methylated CpG islands.

BACKGROUND: Hypermethylation of promoter CpG islands is strongly correlated to transcriptional gene silencing and epigenetic maintenance of the silenced state. As well as its role in tumor development, CpG island methylation contributes to the acquisition of resistance to chemotherapy. Differential Methylation Hybridisation (DMH) is one technique used for genome-wide DNA methylation analysis. The study of such microarray data sets should ideally account for the specific biological features of DNA methylation and the non-symmetrical distribution of the ratios of unmethylated and methylated sequences hybridised on the array. We have therefore developed a novel algorithm tailored to this type of data, Methylation Linear Discriminant Analysis (MLDA). RESULTS: MLDA was programmed in R (version 2.7.0) and the package is available at CRAN 1. This approach utilizes linear regression models of non-normalised hybridisation data to define methylation status. Log-transformed signal intensities of unmethylated controls on the microarray are used as a reference. The signal intensities of DNA samples digested with methylation sensitive restriction enzymes and mock digested are then transformed to the likelihood of a locus being methylated using this reference. We tested the ability of MLDA to identify loci differentially methylated as analysed by DMH between cisplatin sensitive and resistant ovarian cancer cell lines. MLDA identified 115 differentially methylated loci and 23 out of 26 of these loci have been independently validated by Methylation Specific PCR and/or bisulphite pyrosequencing. CONCLUSION: MLDA has advantages for analyzing methylation data from CpG island microarrays, since there is a clear rational for the definition of methylation status, it uses DMH data without between-group normalisation and is less influenced by cross-hybridisation of loci. The MLDA algorithm successfully identified differentially methylated loci between two classes of samples analysed by DMH using CpG island microarrays.

Distinct methylation profiles of glioma subtypes.

Gliomas are tumors of the central nervous system with a wide spectrum of different tumor types. They range from pilocytic astrocytoma, with a generally good prognosis, to the extremely aggressive malignant glioblastoma. In addition to these 2 types of contrasting neoplasms, several other subtypes can be distinguished, each characterized by specific phenotypic, as well as genotypic features. Recently, the epigenotype, as evident from differentially methylated DNA loci, has been proposed to be useful as a further criterion to distinguish between tumor types. In our study, we screened 139 tissue samples, including 33 pilocytic astrocytomas, 46 astrocytomas of different grades, 7 oligoastrocytomas, 10 oligodendrogliomas, 10 glioblastoma multiforme samples and 33 control tissues, for methylation at CpG islands of 15 different gene loci. We used the semiquantitative high throughput method MethyLight to analyze a gene panel comprising ARF, CDKN2B, RB1, APC, CDH1, ESR1, GSTP1, TGFBR2, THBS1, TIMP3, PTGS2, CTNNB1, CALCA, MYOD1 and HIC1. Seven of these loci showed tumor specific methylation changes. We found tissue as well as grade specific methylation profiles. Interestingly, pilocytic astrocytomas showed no evidence of CpG island hypermethylation, but were significantly hypomethylated, relative to control tissues, at MYOD1. Our results show that glioma subtypes have characteristic methylation profiles and, with the exception of pilocytic astrocytomas, show both locus specific hyper- as well as hypomethylation.

SASH1: a candidate tumor suppressor gene on chromosome 6q24.3 is downregulated in breast cancer.

Loss of heterozygosity (LOH) and in silico expression analysis were applied to identify genes significantly downregulated in breast cancer within the genomic interval 6q23-25. Systematic comparison of candidate EST sequences with genomic sequences from this interval revealed the genomic structure of a potential target gene on 6q24.3, which we called SAM and SH3 domain containing 1 (SASH1). Loss of the gene-internal marker D6S311, found in 30% of primary breast cancer, was significantly correlated with poor survival and increase in tumor size. Two SASH1 transcripts of approximately 4.4 and 7.5 kb exist and are predominantly transcribed in the human breast, lung, thyroid, spleen, placenta and thymus. In breast cancer cell lines, SASH1 is only expressed at low levels. SASH1 is downregulated in the majority (74%) of breast tumors in comparison with corresponding normal breast epithelial tissues. In addition, SASH1 is also downregulated in tumors of the lung and thyroid. Analysis of the protein domain structure revealed that SASH1 is a member of a recently described family of SH3/SAM adapter molecules and thus suggests a role in signaling pathways. We assume that SASH1 is a new tumor suppressor gene possibly involved in tumorigenesis of breast and other solid cancers. We were unable to find mutations in the coding region of the gene in primary breast cancers showing LOH within the critical region. We therefore hypothesize that other mechanisms as for instance methylation of the promoter region of SASH1 are responsible for the loss of expression of SASH1 in primary and metastatic breast cancer.