3422 results for "ovarian cancer"

in 5.15 milliseconds.

• Developing therapeutics for ovarian cancer using ovarian cancer organoids

  To identify effective drugs for clear cell ovarian cancer (CCC) and high-grade serous ovarian cancer (HGSC) through high-throughput drug screening using ovarian cancer organoids and to identify novel therapeutic targets based on the biological characteristics of CCC and HGSC through omics analysis.

  Study JGAS000764

• Gene expression profile of mesothelial-derived carcinoma-associated fibroblasts

  RNA-sequencing was carried out on ascetic fluid-isolated mesothelial cells from low-grade serous ovarian cancer patients, high-grade serous ovarian cancer patients, chemotherapy-treated high-grade serous ovarian cancer patients and control mesothelial cells obtained from non-oncologic patients to identify differentially expressed genes associated to mesothelial-to-mesenchymal transition process.

  Study EGAS00001003747

• Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  Ovarian cancer is the leading cause of death from gynecological cancers worldwide. No effective screening methods exist, and tumors are commonly detected at advanced stages where treatment is much less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we detected ovarian cancer with high specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach distinguished benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Study EGAS50000000484

• Identification of genetic mutations characteristic for recurrence of serous ovarian cancer.

  Establishment of novel therapeutic strategy to overcome intractable cancer by molecular profiling of serous ovarian cancer

  Study JGAS000104

• Single cell whole genome sequencing of 5 ovarian cancer specimens

  Single cell whole genome sequencing BAM files for five ovarian cancer specimens.

  Study EGAS50000001458

• Genetic Epidemiology of Ovarian Cancer Histotypes

  Epithelial ovarian cancer is a highly fatal malignancy with known genetic etiology; however, it is estimated that a substantial portion of narrow sense heritability remains to be discovered. The goal of this research was to use genetic information from distantly related ovarian cancer cases to identify regions of the genome that may harbor rare risk variants for epithelial ovarian cancer. The study was conducted in the setting of the Utah Population Database, a statewide data resource in which extensive ancestry data are linked to Utah Cancer Registry records. Focusing on families with a statistically significant excess risk of epithelial ovarian cancer, we used the Infinium Global Screening Array v.3.0 to generate germline genotyping data for distantly related cases. We then applied Shared Genomic Segment Analysis to each set of related cases to identify genomic regions that may harbor ovarian cancer risk variants. Eleven regions were identified. Genotype data are available through dbGaP for one case from each pedigree. Genotype data from other ovarian cancer cases within the high-risk pedigrees as well as the pedigrees' corresponding structures can be requested and made available with approval from the Utah Resource for Genetic and Epidemiologic Research (RGE).

  Study phs003140

• Sequencing data of tumor tissue obtained from GANNET53 study patients

  The GANNET53 clinical trial evaulated novel treatment options for ovarian cancer patients with platinum-resistant relapse. Archival fresh-frozen paraffin embedded tissue was available from 131 of the 133 enrolled patients. NGS sequencing aimed at assessing the mutational spectrum of key ovarian cancer genes (with a focus on TP53), and their relevance for therapy resistance. From available FFPE samples, DNA was extracted and NGS sequenced using the SureSeq™ Ovarian Cancer Panel and the NGS Library Preparation kit covering all exons of 7 key ovarian cancer genes BRCA1, BRCA2,TP53, PTEN, ATM, ATR, NF1 for single nucleotide variants (SNV) and indels. Finally, sequence data from 118 individual FFPE tumor tissue samples were generated.

  Study EGAS50000000935

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• SCANDARE ovarian

  Prospective biobanking study in ovarian cancer patients aiming at better understand the link between the molecular alterations of the tumor itself, its microenvironment and immune response.

  Study EGAS50000001161

• Improved T Cell Immunity Following Neoadjuvant Chemotherapy in Ovarian Cancer

  This study characterized the evolution of the peripheral immune cell function and composition across the course of standard of care platinum and taxane chemotherapy in ovarian cancer using bulk and single cell transcriptomic approaches. Serial blood samples were collected from ten patients with advanced high-grade serous ovarian cancer treated with chemotherapy. Single cell sequencing was performed on five patients' samples collected before the initiation of chemotherapy and after the third cycle of chemotherapy.

  Study phs002862