Similar Datasets
Project description:Epigenomic and transcriptomic analyses of epithelial ovarian cancer
| PRJNA495805 | ENA
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.
2013-06-05 | E-GEOD-47633 | biostudies-arrayexpress
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.
2013-06-05 | GSE47633 | GEO
Project description:CCCTC-binding factor (CTCF) is an 11 zinc fingers transcription factor that functions as both an oncogenic and tumor suppressor, depending on the cancer types, through epigenetic regulation. Epigenetic regulation including DNA methylation and histone modifications are critically involved in cancer metastasis. We then hypothesized that CTCF might play a vital role in epithelial ovarian cancer metastasis. Firstly, we found that CTCF expression was elevated in ovarian cancer tissues compared to non-tumor tissues. The elevated expression of CTCF predicts poor prognosis of ovarian cancer patients. Then, we revealed that CTCF knockdown significantly inhibited the migration, invasion and metastasis of ovarian cancer cells, although it had no effect on cell proliferation and tumor growth, which have been demonstrated with both in vitro and in vivo experiments. More importantly, we observed a higher CTCF expression in metastatic lesions than that in primary lesions from ovarian cancer patients. Mechanically, PCR array demonstrated that CTCF might regulate a series of metastasis associated genes, including CTBP1, SERPINE1 and SRC. Finally, we observed positive correlations between CTCF expression and those three genes in epithelial ovarian cancer specimens. In conclusion, this study demonstrates that CTCF is an oncogene in ovarian cancer to promote tumor metastasis through broadly controlling the expression of metastasis-associated genes. Our findings suggest CTCF could be a novel drug target to treat ovarian cancer by interfering with cancer cell metastasis.
2016-09-01 | GSE85453 | GEO
Project description:Protein biomarkers of early stages of disease are critical for managing the disease and improving outcomes. Unfortunately, discovery of protein biomarkers is hampered by the limited availability of assays for sensitive and reproducible quantification of proteins in complex biological matrices such as blood plasma. In the recent years, Selected Reaction Monitoring (SRM) has emerged as a robust mass spectrometric method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing protein biomarkers for epithelial ovarian cancer, and illustrate the extent to which SRM platform, combined with sound experimental design and statistical analysis, results in robust detection of predictive analytes. First, the biomarker development was guided by a discovery-driven proteomic effort to detect potential N-glycoprotein biomarker candidates in tissue of a genetically stable ovarian cancer mouse model. Next, 65 candidate markers were reproducibly quantified with SRM assays across a large cohort of over 200 plasma samples from ovarian cancer patients and healthy controls. Finally, these measurements were used to derive 5-protein signatures for distinguishing individuals with epithelial ovarian cancer from healthy controls. The sensitivity of the candidate biomarker signature in combination with CA125 ELISA-based measurements currently used in clinic, exceeded that of CA125 ELISA-based measurements alone. The SRM-based strategy in this study is broadly applicable. It can be used in any study that requires accurate and reproducible quantification of selected proteins in a high-throughput and multiplexed fashion.
2019-07-02 | MSV000084048 | MassIVE
Project description:The immune system is active in the tumor microenvironment (TME) of epithelial ovarian cancer (EOC) and carries both effector and suppressive functions. We profiled biomarker expression on serial biological specimens collected during intraperitoneal (IP) chemotherapy to better define treatment-induced tumor involution.
2023-06-02 | GSE217178 | GEO
Project description:The immune system is active in the tumor microenvironment (TME) of epithelial ovarian cancer (EOC) and carries both effector and suppressive functions. We profiled biomarker expression on serial biological specimens collected during intraperitoneal (IP) chemotherapy to better define treatment-induced tumor involution.
2023-06-02 | GSE217177 | GEO
Project description:The immune system is active in the tumor microenvironment (TME) of epithelial ovarian cancer (EOC) and carries both effector and suppressive functions. We profiled biomarker expression on serial biological specimens collected during intraperitoneal (IP) chemotherapy to better define treatment-induced tumor involution.
2023-06-02 | GSE217175 | GEO
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.
2020-07-23 | GSE154890 | GEO
Project description:To improve our understanding of ovarian cancer, we performed genome-wide analyses of 45 ovarian cancer cell lines. Given the challenges of genomic analyses of tumors without matched normal samples, we developed approaches for detection of somatic sequence and structural changes and integrated these with epigenetic and expression alterations. Alterations not previously implicated in ovarian cancer included amplification or overexpression of ASXL1 and H3F3B, deletion or underexpression of CDC73 and TGF-beta receptor pathway members, and rearrangements of YAP1-MAML2 and IKZF2-ERBB4. Dose-response analyses to targeted therapies revealed unique molecular dependencies, including increased sensitivity of tumors with PIK3CA and PPP2R1A alterations to PI3K inhibitor GNE-493, MYC amplifications to PARP inhibitor BMN673, and SMAD3/4 alterations to MEK inhibitor MEK162. Genome-wide rearrangements provided an improved measure of sensitivity to PARP inhibition. This study provides a comprehensive and broadly accessible resource of molecular information for the development of therapeutic avenues in ovarian cancer.
| S-EPMC6481945 | biostudies-literature