Epigenetic analysis of the Notch superfamily in high-grade serous ovarian cancer
Gene methylation and other epigenetic modifications of gene regulation have been implicated in the growth of ovarian cancer, but the clinical significance of such modifications in the Notch pathway in high-grade serous ovarian cancer (HGS-OvCa) is not well understood. We used The Cancer Genome Atlas (TCGA) data to study the clinical relevance of epigenetic modifications of Notch superfamily genes.Methods
We analyzed the interaction of DNA methylation and miRNAs with gene expression data for Notch superfamily members with the Spearman rank correlation test and explored potential relationships with overall survival (OS) with the log-rank test. We downloaded clinical data, level 3 gene expression data, and level 3 DNA methylation data for 480 patients with stage II–IV HGS-OvCa from the TCGA data portal. Patients were randomly divided into training and validation cohorts for survival analyses. In each set, patients were grouped into percentiles according to methylation and microRNA (miRNA) or messenger RNA (mRNA) levels. We used several algorithms to predict miRNA–mRNA interaction.ResultsThere were significant inverse relationships between methylation status and mRNA expression for PPARG, CCND1, and RUNX1. For each of these genes, patients with a lower methylation level and higher expression level had significantly poorer OS than did patients with a higher methylation level and lower expression level. We also found a significant inverse relationship between miRNAs and mRNA expression for CCND1, PPARG, and RUNX1. By further analyzing the effect of miRNAs on gene expression and OS, we found that patients with higher levels of CCND1, PPARG, and RUNX1 expression and lower expression levels of their respective miRNAs (502-5p, 128, and 215/625) had significantly poorer OS.Conclusions
Epigenetic alterations of multiple Notch target genes and pathway interacting genes (PPARG, CCND1, and RUNX1) may relate to activation of this pathway and poor survival of patients with HGS-OvCa.
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ABSTRACT: Ovarian cancer is the most lethal of all gynecologic malignancies because women commonly present with advanced stage disease and develop chemotherapy refractory tumors. While cytoreductive surgery followed by platinum based chemotherapy are initially effective, ovarian tumors have a high propensity to recur highlighting the distinct need for novel therapeutics to improve outcomes for affected women. The Notch signaling pathway plays an established role in embryologic development and deregulation of this signaling cascade has been linked to many cancers. Recent genomic profiling of serous ovarian carcinoma revealed that Notch pathway alterations are among the most prevalent detected genomic changes. A growing body of scientific literature has confirmed heightened Notch signaling activity in ovarian carcinoma, and has utilized in vitro and in vivo models to suggest that targeting this pathway with gamma secretase inhibitors (GSIs) leads to anti-tumor effects. While it is currently unknown if Notch pathway inhibition can offer clinical benefit to women with ovarian cancer, several GSIs are currently in phase I and II trials across many disease sites including ovary. This review will provide background on Notch pathway function and will focus on the pre-clinical literature that links altered Notch signaling to ovarian cancer progression.Journal of Ovarian Research 11/2014; 7(1):95. · 2.03 Impact Factor
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ABSTRACT: MicroRNAs (miRNAs, miRs) are non-coding RNAs which post-transcriptionally regulate mRNA synthesis. Data regarding the expression and clinical relevance of miRNAs and the miRNA-regulating machinery in ovarian carcinoma has been rapidly expanding in recent years. This review presents current knowledge in this area. PubMed search was undertaken using the terms 'ovarian' and 'microRNA' RESULTS: A total of 492 papers were identified, of which approximately 100 were publications in English focusing exclusively or partly on clinical ovarian carcinoma specimens. These studies have identified multiple miRNAs with a potential role in the diagnosis, biology and progression of ovarian carcinoma, as well as on predicting chemoresponse and determining prognosis. The presented data support a clinical role for miRNAs in ovarian carcinoma and suggest that miRNA-regulated pathways may be of relevance for novel therapeutics. Novel technologies offer new possibilities for wide-scale miRNA-based classification of OC. Further genomic research focusing on larger series of tumors of similar histological type in combination with experimental approaches is likely to expand our understanding of the role of miRNAs in this cancer.Gynecologic Oncology 04/2014; · 3.69 Impact Factor
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ABSTRACT: Recent method development has included multi-dimensional genomic data algorithms because such methods have more accurately predicted clinical phenotypes related to disease. This study is the first to conduct an integrative genomic pathway-based analysis with a graph-based learning algorithm. The methodology of this analysis, graph-based semi-supervised learning, detects pathways that improve prediction of a dichotomous variable, which in this study is cancer stage. This analysis integrates genome-level gene expression, methylation, and single nucleotide polymorphism (SNP) data in serous cystadenocarcinoma (OV) and colon adenocarcinoma (COAD). The top 10 ranked predictive pathways in COAD and OV were biologically relevant to their respective cancer stages and significantly enhanced prediction accuracy and area under the ROC curve (AUC) when compared to single data-type analyses. This method is an effective way to simultaneously predict binary clinical phenotypes and discover their biological mechanisms.Cancer informatics 01/2014; 13(Suppl 4):1-9.