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Epigenomic and transcriptomic analyses of epithelial ovarian cancer

ABSTRACT: Epigenomic and transcriptomic analyses of epithelial ovarian cancer

PROVIDER: PRJNA495805 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR8030170.fastq.gz	Fastqsanger.gz
	SRR8030180.fastq.gz	Fastqsanger.gz
	SRR8030190.fastq.gz	Fastqsanger.gz
	SRR8030200.fastq.gz	Fastqsanger.gz
	SRR8030210_1.fastq.gz	Fastqsanger.gz

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Project description:Background Environmental health research has recently undergone a dramatic shift, with ongoing technological advancements allowing for broader coverage of exposure and molecular biology signatures. Approaches to integrate such measures are still needed to increase understanding between systems-level exposure and biology. Objectives We address this gap by evaluating placental tissues to identify novel chemical-biological interactions associated with preeclampsia. This study tests the hypothesis that understudied chemicals are present in the human placenta and associated with preeclampsia-relevant disruptions, including overall case status (preeclamptic vs. normotensive patients) and underlying transcriptomic/epigenomic signatures. Methods A non-targeted analysis based on high-resolution mass spectrometry was used to analyze placental tissues from a cohort of 35 patients with preeclampsia (n = 18) and normotensive (n = 17) pregnancies. Molecular feature data were queried against chemicals within the U.S. Environmental Protection Agency’s DSSTox database, and prioritized for confirmation based on association with preeclampsia case status and confidence of chemical identification. All molecular features were evaluated for relationships to mRNA, microRNA, and CpG methylation (i.e., multi-omic) signature alterations involved in preeclampsia. Results A total of 183 molecular features were identified with significantly differentiated abundance in placental extracts of preeclamptic patients; these features clustered into distinct chemical groupings using unsupervised methods. Of these features, 53 were identified (mapping to 40 distinct chemicals) using chemical standards, fragmentation spectra, and chemical metadata. In general, human metabolites had the largest feature intensities and strongest associations with preeclampsia-relevant multi-omic changes. Exogenous drugs were second most abundant and had fewer associations with multi-omic changes. Other exogenous chemicals (non-drugs) were least abundant and had the fewest associations with multi-omic changes. Conclusions These global data trends suggest that human metabolites are heavily intertwined with biological processes involved in preeclampsia etiology, while exogenous chemicals may still impact select transcriptomic/epigenomic processes. This study serves as a demonstration of merging systems exposures with systems biology to better understand chemical-disease relationships.

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Epigenomic and transcriptomic analyses of epithelial ovarian cancer

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