Genetic Epidemiology of Ovarian Cancer Histotypes
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ABSTRACT:
PROVIDER: PRJNA906705 | ENA |
REPOSITORIES: ENA
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Project description:Genetic Epidemiology of Ovarian Cancer Histotypes
| PRJNA906704 | ENA
Project description:Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (rg) between endometriosis and clear cell (rg=0.71), endometrioid (rg=0.48) and high-grade serous (rg=0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identify 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases.
2022-03-07 | GSE197928 | GEO
Project description:Ovarian cancer is the eight most common cancer in the women and the deadliest gynecologic malignancy. The majority of patients (90%) are diagnosed with epithelial ovarian cancer (EOC), which is comprised by five main histotypes – high-grade serous ovarian carcinoma (HGSC), low-grade serous ovarian carcinoma (LGSC), endometrioid ovarian carcinoma (EC), mucinous ovarian carcinoma (MC), and clear cell ovarian carcinoma (CCC). The established diagnostic biomarker CA-125 is unspecific and has been shown to not be suitable for early detection. Due to limited diagnostic tools and EOC being asymptomatic in early stages (I-II), 70% of patients are diagnosed in late stages (III-IV) and therefore the disease is associated with poor prognosis. Although the histotypes have distinct clinicopathologic characteristics, first line treatment has remained the same the last four decades regardless of histotype. In this study, we aimed to profile the phosphorylated proteins of primary tumors from a cohort of 180 EOC patients comprising HGSC, EC, MC, and CCC across all stages.
2026-08-13 | PXD069845 | Pride
Project description:Ovarian cancer is a common, malignant cancer in the female reproductive system. Despite the commonly affected tissue ovary, ovarian cancer is a heterogeneous disease consisting of at least five different histological subtypes and varying clinical features, cells of origin, molecular composition, risk factors, and treatments. With cumulative studies on the tumor microenvironment, a comprehensive landscape of the constituent cell types, and their interactions are yet to be established in ovarian cancer and its histotypes. Further characterization of tumor progression, metastasis, and various histotypes is needed to connect molecular signatures to pathological grading for tailored diagnosis and treatment. In this study, we leveraged high-resolution single-cell RNA sequencing technology to elucidate the cellular compositions on 21 solid tumor samples collected from 12 patients with six ovarian cancer histotypes and both primary (ovaries) and metastatic (omentum, rectum) sites. The diverse collection allows us to zoom in on histotype and tumor site-specific expression patterns of cells in the tumor and identify key marker genes and ligand-receptor pairs that are active in the ovarian tumor microenvironment. Our findings can be used in improving disease stratification and design of customized treatment.
2023-12-15 | GSE235931 | GEO
Project description:A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes
| PRJNA812889 | ENA
Project description:Exploring the tumor micro-environment of ovarian cancer histotypes and tumor sites
| PRJNA988051 | ENA
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes.
2012-10-25 | GSE30284 | GEO
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes.
2012-10-25 | GSE30274 | GEO
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes.
2012-10-25 | GSE30300 | GEO
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes.
2012-10-25 | GSE30283 | GEO