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Differential DNA Methylation in High Grade Serous Ovarian Cancer (HGSOC) is associated with Tumor Behavior

ABSTRACT: Introduction/ Background: The epigenome represents and adds another facet of complexity to cancer that needs to be understood to categorize patients into those at risk of disease, recurrence, or treatment failure. Our goal is to compare DNA methylation status between controls vs HGSOC, and relate it with clinical outcomes. Methodology: A retrospective review of our institution’s advanced/ recurrent HGSOC patients yielded 99 cases with good quality DNA and RNA. 12 normal fallopian tubes were also collected and used as controls. Infinium Illumina methylationEPIC was used to characterize DNA methylation status and RNA seq to evaluate gene expression. T- tests were used to compare methylation patterns between controls vs HGSOC, primary vs recurrent, and optimal vs suboptimal surgical outcomes. Spearman’s rank correlation was used to evaluate association between degree of methylation and expression of identified genes. Validation of our findings used the cancer genome atlas (TCGA) database followed by C-statistics to assess degree of agreement. Results: Out of 66,069 methylation probes that interrogate known genes, 5,852 probes were significantly different between normal and HGSOC. This includes genes that are enriched in several pathways such as the RAS signaling pathway. A similar analysis of the TCGA database showed 2,075 differentially methylated probes. 1,891 probes were significant in both datasets giving a 70.1% degree of agreement. When comparing differential DNA methylation between primary and recurrent disease, there were 57 probes which represent 17 genes that were significantly different. When comparing optimal vs suboptimal surgical outcomes, 99 probes were significantly different wherein 29 genes show expected inverse correlation between methylation status and gene expression. Conclusions: There are significant differences in methylation patterns between HGSOC and fallopian tubes, primary vs recurrent tissues, and optimal vs sub-optimal surgical outcomes. Cataloging these phenomena in a well characterized clinical population will aid in determining groupings for precision medicine treatment cohorts in the future.

ORGANISM(S): Homo sapiens

PROVIDER: GSE133556 | GEO | 2019/07/01

REPOSITORIES: GEO

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Project description:Whole-genome gene expression analysis has been successfully utilized to diagnose, prognosticate, and identify potential therapeutic targets for cardiovascular disease. However, the utility of this approach to identify outcome-related genes and dysregulated pathways following first-time myocardial infarction (AMI) remains unknown and may offer a novel strategy to detect affected expressome networks that predict long-term outcome. Whole-genome microarray and targeted cytokine expression profiling on blood samples from normal cardiac function controls and first-time AMI patients within 48-hours post-MI revealed expected differential gene expression profiles enriched for inflammation and immune-response pathways in AMI patients. To determine molecular signatures at the time of AMI that could prognosticate long-term outcomes, transcriptional profiles from sub-groups of AMI patients with (n=5) or without (n=22) any recurrent events over an 18-month follow-up were compared. This analysis identified 559 differentially expressed genes. Bioinformatic analysis of this differential gene set for associated pathways revealed 1) increasing disease severity in AMI patients is associated with a decreased expression of the developmental epithelial-to-mesenchymal transition, and 2) modulation of cholesterol transport genes that include ABCA1, CETP, APOA1, and LDLR is associated with clinical outcome. In conclusion, differentially regulated genes and modulated pathways were identified that predicted recurrent cardiovascular outcomes in first-time AMI patients. This cell-based approach for risk stratification in AMI warrants a larger study to determine the role of metabolic remodeling and regenerative processes required for optimal outcomes. A validated transcriptome assay could represent a novel, non-invasive platform to anticipate modifiable pathways and therapeutic targets to optimize long-term outcome for AMI patients. The overall experimental design includes blood samples from 21 control and 31 myocardial infaction patient groups. Among the 31patients, 5 patients have recurrent events. Microarray were peformed on the blood samples and comparisons of control vs patient and patients with recurrent events vs patients without recurrent events were performed to identify differential genes related to disease or patients groups with recurrent events for the following bioinformatic analysis.

Project description:High-grade serous ovarian cancer (HGSOC) exhibits significant genomic heterogeneity within a patient at presentation. Recent work has suggested that this heterogeneity is linked to the development of resistance and disease progression in that chemotherapy selects for minor resistant subclones embodied in presentation disease leading to short progression-free survival and resistant relapse. Cell line models support this by showing that relapse is not an immediate descendant of presentation disease, but so far no immediate clinical evidence has been provided that convincingly demonstrates the origin of relapse. It is further still unclear what evolutionary processes shape the mutational landscape of HGSOC in vivo and to what extent the degree of genomic heterogeneity impacts a patient's clinical outcome. We address these questions by inferring evolutionary trees of metastatic disease from structural variations between 138 cancer samples obtained from 17 patients undergoing neoadjuvant chemotherapy for HGSOC. Using novel phylogenetic methods, we quantify genomic changes in the course of chemotherapy and the degree of clonal expansion and show that these indices determine patient outcome with high accuracy. We demonstrate that relapse is indeed a minor subclone of presentation disease by verifying that the focal NF1 deletion of a relapse case was already present at biopsy. By leveraging the information contained in the evolutionary trees, we unveil the etiology of genetic heterogeneity and the tumorigenic potential of HGSOC cell populations. This is the first comprehensive study showing the origin, strength and effect of genetic heterogeneity in HGSOC in a clinical setting. In addition to its immediate clinical significance, it strengthens previous statements that single sample biopsies are seemingly insufficient to predict disease progression and stresses the importance of establishing multiple sampling as a routine approach in the clinic. Clinical data and tissue samples were collected on the prospective CTCR-OV03 and CTCR-OV04 clinical studies designed to identify biomarkers of heterogeneity.

Project description:Background: Despite an early response to platinum-based chemotherapy in advanced stage high-grade serous ovarian cancer (HGSOC), the majority of patients will relapse with drug-resistant disease. Aberrant epigenetic alterations like DNA methylation are common in HGSOC. Differences in DNA methylation are associated with chemoresponse in these patients. The objective of this study was to identify and validate novel epigenetic markers of chemoresponse using genome-wide analysis of DNA methylation in extreme chemoresponsive HGSOC patients. Methods: Genome-wide next-generation sequencing was performed on methylation-enriched tumor DNA of two HGSOC patient groups with residual disease, extreme responders (≥18 months progression-free survival (PFS), n = 8) and non-responders (≤6 months PFS, n = 10) to platinum-based chemotherapy. DNA methylation and expression data of the same patients were integrated to create a gene list. Genes were validated on an independent cohort of extreme responders (n = 21) and non-responders (n = 31) using pyrosequencing and qRT-PCR. In-silico validation was performed using publicly available DNA methylation (n = 91) and expression (n = 208) datasets of unselected advanced stage HGSOC patients. Functional validation of FZD10 on chemosensitivity was done in ovarian cancer cell lines using siRNA-mediated silencing. Results: Integrated genome-wide methylome and expression analysis identified 45 significantly differentially methylated and expressed genes between two chemoresponse groups. Four genes FZD10, FAM83A, MYO18B and MKX were successfully validated in an external set of extreme chemoresponsive HGSOC patients. High FZD10 and MKX methylation was related with extreme responders and high FAM83 and MYO18B methylation with extreme non-responders. In publicly available advanced stage HGSOC datasets, FZD10, MYO18B and MKX methylation levels were associated with PFS. High FZD10 methylation was strongly associated with improved PFS [HR=0.43, 95%CI=0.27-0.65, p=0.0002]. Consistently, low FZD10 expression was associated with improved PFS [HR=1.36, 95%CI=0.99-1.88, p=0.058]. FZD10 silencing caused significant sensitization towards cisplatin treatment in survival assays and apoptosis assays. Conclusions: By applying genome-wide integrated methylome analysis on extreme chemoresponsive HGSOC patients, we identified novel clinically relevant, epigenetically-regulated markers of platinum-sensitivity in HGSOC patients. The clinical potential of these markers in predictive and therapeutic approaches has to be further validated in prospective studies.

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Differential DNA Methylation in High Grade Serous Ovarian Cancer (HGSOC) is associated with Tumor Behavior

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