Similar Datasets
Project description:RNA-Seq of pre-chemo high-grade serous ovarian tumors
| PRJNA671754 | ENA
Project description:Our data suggest that neoadjuvant chemotherapy enhances anti-cancer responses of T cells in peritoneal metastases of patients with high-grade serous ovarian cancer but does not decrease levels of immune checkpoint molecules, providing a rationale for sequential chemo-immunotherapy. tRNA was isolated from 35 omental tissue samples of HGSOC metastases either pre or post NACT treatment. RNASeq was performed on poly-A selected mRNA fragments, 100 b.p paired end, and strand specific, on average 40 million reads per sample.
2016-07-27 | E-GEOD-71340 | biostudies-arrayexpress
Project description:High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterised by ubiquitous TP53 mutation, profound structural variation and heterogeneity. Multiple mutational processes driving chromosomal instability can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs) and provide detailed transcriptomic and genomic profiles using shallow whole genome sequencing single cell and bulk analysis. We show that PDOs comprise communities of different clonal populations and represent models of CCNE1 amplification, chromothripsis, tandem-duplicator phenotype and whole genome duplication. PDOs can also be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide a genomic tool for studies of specific mutational processes and precision therapeutics.
2022-07-17 | GSE208216 | GEO
Project description:High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecologic neoplasm, with five-year survival rate below 30%. Early disease detection is of utmost importance to improve the cure rate of HGSOC. Liquid biopsies are now becoming a new paradigm to develop novel biomarkers with diagnostic and prognostic purposes. The focus of this study was to detect the levels of circulating miRNAs in tissues and sera from patients with HGSOC and to evaluate their diagnostic value. To this end, an array-based discovery platform, followed by an innovative statistical approach of data normalization, was exploited, to identify miRNA species selectively expressed in serum of patients with HGSOC. Sera from 106 high grade serous ovarian carcinoma (HGSOC) and 24 healthy controls were used for profiling serum microRNA using a modified version of a commercially available microarray, with the aim of identifying differentially expressed microRNA between tumor patients and healthy controls.
2017-01-30 | E-MTAB-4667 | biostudies-arrayexpress
Project description:To improve our understanding of the molecular basis of chemo-refractory high grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two independent validation cohorts (spanning four academic centers) and utilizing two biospecimen types (formalin-fixed paraffin-embedded and frozen tumor biopsies). As the largest and most comprehensive study of refractory ovarian cancers to date, this effort identified a 64-protein signature that predicts a subset of HGSOCs refractory to initial platinum-based therapy with high specificity and is validated in two independent patient cohorts. We also detected significant association between lack of Ch17 loss-of-heterozygosity and refractory disease. Moreover, based on protein pathway expression, five novel clusters of HGSOC were identified and validated across two independent patient cohorts, as well as in patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic targets.
2023-09-18 | PXD040742 | panorama
Project description:Tumor infiltrating lymphocytes (TILs) play a significant role in the tumor microenvironment in high-grade serous ovarian cancer (HGSOC). To better understand the interactions and functions of TILs in HGSOC progression, we performed proteogenomic profiling of TILs in 65 tumors collected from 12 HGSOC patients.
2024-03-15 | PXD045710 | Pride
Project description:Multiple studies have identified transcriptome subtypes of high-grade serous ovarian carcinoma (HGSOC), but their interpretation and translation are complicated by tumor evolution and polyclonality accompanied by extensive accumulation of somatic aberrations, varying cell type admixtures, and different tissues of origin. In this study, we examined the chronology of HGSOC subtype evolution in the context of these factors using a novel integrative analysis of absolute copy number analysis and gene expression in The Cancer Genome Atlas complemented by single-cell analysis of six independent tumors. Tumor purity, ploidy, and subclonality were reliably inferred from different genomic platforms, and these characteristics displayed marked differences between subtypes. Genomic lesions associated with HGSOC subtypes tended to be subclonal, implying subtype divergence at later stages of tumor evolution. Subclonality of recurrent HGSOC alterations was evident for proliferative tumors, characterized by extreme genomic instability, absence of immune infiltration, and greater patient age. In contrast, differentiated tumors were characterized by largely intact genome integrity, high immune infiltration, and younger patient age. Single-cell sequencing of 42,000 tumor cells revealed widespread heterogeneity in tumor cell type composition that drove bulk subtypes but demonstrated a lack of intrinsic subtypes among tumor epithelial cells. Our findings prompt the dismissal of discrete transcriptome subtypes for HGSOC and replacement by a more realistic model of continuous tumor development that includes mixtures of subclones, accumulation of somatic aberrations, infiltration of immune and stromal cells in proportions correlated with tumor stage and tissue of origin, and evolution between properties previously associated with discrete subtypes.
2020-07-17 | GSE154600 | GEO
Project description:We measured gene expression in single-cell RNA sequencing samples from patients with high-grade serous ovarian cancer (HGSOC), for a study on improving HGSOC subtype definition by taking into account varying cell type proportions within tumors.
2020-10-03 | GSE158937 | GEO
Project description:Ovarian cancer (OV) is the leading cause of mortality from gynaecological malignancies with poor prognosis and limited therapeutic options. Prevalent copy number alteration (CNA) is a genetic characteristic of OV, but its contribution to tumorigenesis remain unclear. Here, we identify RAD21, a component of the cohesin complex, as a frequently amplified and overexpressed oncogene in high grade serous ovarian cancer (HGSOC), the most common subtype of OV. RAD21 copy number amplification and overexpression are correlated with poor prognosis in HGSOC. In HGSOC cells and xenograft models, depletion of RAD21 inhibited cell proliferation by inducing mitotic phase arrest and thereby reducing tumour growth, whereas overexpression of RAD21 conferred resistance to carboplatin. Mechanistically, we found that RAD21 interacts with YAP/TEAD4 transcriptional co-repressors and recruits NuRD complex to suppress the downstream targets. Additionally, genetic and pharmacologic inhibition of YAP disrupts the co-repressor complex to suppress the oncogenic activity of RAD21 and recapitulates the phenotypes of RAD21 depletion in HGSOC. Therefore, our work sheds light on the oncogenic role of frequent CNAs and identifies a previously unrecognized role of RAD21/YAP complex which contributes to tumorigenesis and chemo-resistance in HGSOC.
2023-04-10 | GSE156845 | GEO
Project description:Bulk and single-cell RNA sequencing do not provide full characterization of tissue spatial diversity in cancer samples, and currently available in situ techniques (multiplex immunohistochemistry, imaging mass cytometry) allow for only limited analysis of a small number of targets. The current study represents the first comprehensive approach to spatial transcriptomics of high-grade serous ovarian carcinoma using intact tumor tissue. We selected a small cohort of patients with highly annotated high-grade serous ovarian carcinoma, categorized them by response to neoadjuvant chemotherapy (poor or excellent), and analyzed pre-treatment tumor tissue specimens. Our study uncovered extensive differences in tumor composition between the poor responders and excellent responders to chemotherapy, related to cell cluster organization and localization. This in-depth characterization of high-grade serous ovarian carcinoma tumor tissue from poor and excellent responders showed that spatial interactions between cell clusters may influence chemo-responsiveness more than cluster composition alone.
2021-12-02 | GSE189843 | GEO