Project description:Ovarian aging is characterized by the progressive depletion of primordial follicle reserve, leading to irregular patterns of ovulation and menopause. The basic mechanisms that underlie the ovarian aging and follicle decline is unknown. We sought to explore the role of cellular senescence and epigenomic mechanisms in ovarian aging. Here, we present the transcriptomic changes observed in the ovaries with age using the age groups 3mo, 6mo, 9mo and 12mo (n=5 per group except for 12mo which has an n=4). The age groups capture timepoints from sexual maturation to reproductive health decline.
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.
Project description:Endometriosis, a benign inflammatory disease whereby endometrial-like tissue grows outside the uterus, is a risk factor for endometriosis-associated ovarian cancers. In particular, ovarian endometriomas, cystic lesions of deeply invasive endometriosis, are considered the precursor lesion for ovarian clear-cell carcinoma (OCCC). To explore the transcriptomic landscape, OCCC from women with pathology-proven concurrent endometriosis (n = 4) were compared to benign endometriomas (n = 4) by bulk RNA and small-RNA sequencing.
Project description:We reveal three-dimensional patterns of tumour growth by exploiting the unique metastasizing patterns of treatment naïve stage IIIC/IV epithelial ovarian cancer. We performed topographic mapping of structural genomic rearrangements, coding mutations, copy number changes and RNA expression in biopsies derived from 27 primary and metastatic sites across three patients. Based on somatic genomic changes, we performed sample clustering and obtained unique insight in natural tumour growth and spread. Based on extensive multi-level profiling, our data highlight the diverse modes of epithelial ovarian cancer development before applying selective pressure from therapy. We performed SNP array analysis on tumor biopsies from 3 patients (P1, P2, P3) with advanced stage ovarian cancer. This submission includes SNP data for 26 tumor biopsies and 5 normal tissue samples.
Project description:In the current study we performed characterization of 18 different in vitro models of high-grade serous (HGSOC), low-grade serous (LGSOC), mucinous (MOC), endometrioid (ENOC) and clear cell (CCOC) carcinoma. This study seeks to fill in this gap by generating an integrative Ovarian Cancer Regulatory Atlas (OCRA) of 18 ovarian normal and cancer cells profiled for epigenomic, transcriptomic, chromatin state and chromatin looping signatures.
Project description:We reveal three-dimensional patterns of tumour growth by exploiting the unique metastasizing patterns of treatment naïve stage IIIC/IV epithelial ovarian cancer. We performed topographic mapping of structural genomic rearrangements, coding mutations, copy number changes and RNA expression in biopsies derived from 27 primary and metastatic sites across three patients. Based on somatic genomic changes, we performed sample clustering and obtained unique insight in natural tumour growth and spread. Based on extensive multi-level profiling, our data highlight the diverse modes of epithelial ovarian cancer development before applying selective pressure from therapy.