3288 results for "ovarian cancer"

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• APOLLO-OV: Applied Proteogenomics of High Grade Serous Ovarian Carcinoma

  APOLLO is a proteogenomic study seeking to describe the major genome, transcriptome, proteome and phosphoproteome alterations, subtypes, and molecular predictors of patient outcomes. This study includes 70 high grade serous ovarian carcinoma tissues from the Gynecologic Cancer Center of Excellence (https://medschool.usuhs.edu/gso/research/gyn-cancer-center-of-excellence). Bulk and laser microdissection enriched tumor tissues were profiled by whole genome sequencing, transcriptome sequencing, MS-based proteomics and reverse phase protein arrays. Clinical and sample data include survival times, patient features, and tumor characteristics.

  Study phs003488

• To determine the genomic profile of Triple Negative Breast Cancer patient-derived xenografts (PDX cohort)

  Specific BRCA and immune configurations determine optimal response to platinum-based chemotherapy in triple negative breast and ovarian carcinomas (PDX_WGS)

  Study EGAS00001005995

• Prediction of DNA Repair Inhibitor Response in Short Term Patient-Derived Ovarian Cancer Organoids

  In this study, 34 ovarian tumor organoids generated from 23 patients underwent paired DNA damage repair defect functional analyses and whole exome sequencing analysis to compare genetic mutational status to DNA repair functional capacity. 22 of the patients had high grade serous cancer and 1 of the patients had low grade serous cancer. A normal control, fresh parent tumor, and cells from the organoid culture generated from the parent tumor underwent whole exome sequencing analysis and the data from the sequencing analysis is provided here.

  Study phs001685

• Longitudinal single-cell RNA-seq data of metastatic ovarian cancer

  Study EGAS00001005006

• Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

  Study EGAS00001000135

• Influence of Genomic Landscape on Cancer Immunotherapy for Newly Diagnosed Ovarian Cancer: Biomarker Analyses from the IMagyn050 Randomized Clinical Trial

  The IMagyn050 trial (NCT03038100), which evaluated the efficacy of Atezo vs placebo (Pla) with carboplatin, paclitaxel and bevacizumab (CPB) in front line ovarian cancer patient (pts), did not meet its co-primary endpoints of PFS in ITT or PD-L1+ (Moore et al. JCO 2021). The aim of this exploratory study was to evaluate whether patients with BRCA1/2-mutated or homologous recombination-deficient (HRD) ovarian cancers benefitted from atezolizumab in the phase III IMagyn050 (NCT03038100) trial. Methods: Patients with newly diagnosed ovarian cancer were randomized to either atezolizumab or placebo with standard chemotherapy and bevacizumab. PD-L1 status of tumor-infiltrating immune cells was determined centrally (VENTANA SP142 assay). Genomic alterations, including deleterious BRCA1/2 alterations, genomic loss of heterozygosity (gLOH), tumor mutation burden (TMB), and microsatellite instability (MSI), were evaluated using the FoundationOne assay. HRD was defined as gLOH ≥16%, regardless of BRCA1/2 mutation status. Potential associations between progression-free survival (PFS) and genomic biomarkers were evaluated using standard correlation analyses and log-rank of Kaplan-Meier estimates. Results Among biomarker-evaluable samples, 22% (234/1050) harbored BRCA1/2 mutations and 46% (446/980) were HRD. Median TMB was low irrespective of BRCA1/2 or HRD. Only 3% (29/1024) had TMB ≥10 mut/Mb and 0.3% (3/1022) were MSI-high. PFS was better in BRCA2-mutated versus BRCA2-non-mutated tumors and in HRD versus proficient tumors. PD-L1 positivity (≥1% expression on immune cells) was associated with HRD but not BRCA1/2 mutations. PFS was not improved by adding atezolizumab in BRCA2-mutated or HRD tumors; there was a trend toward enhanced PFS with atezolizumab in BRCA1-mutated tumors. Conclusion Most ovarian tumors have low TMB despite BRCA1/2 mutations or HRD. Neither BRCA1/2 mutation nor HRD predicted enhanced benefit from atezolizumab. This is the first randomized double-blind trial in ovarian cancer demonstrating that genomic instability triggered by BRCA1/2 mutation or HRD is not associated with improved sensitivity to immune checkpoint inhibitors.

  Study EGAS00001006838

• DNA methylation database for gynecological cancer detection, classification and assay development

  DNA methylation changes are associated with cancer the best predictor of the presence of cancer. In order to detect and classify gynecological cancer, we performed MeD-seq to generate DNA methylation profiles of vulvar, cervical, endometrial, fallopian tube and ovarian cancers and their associated healthy tissues. DNA methylation profiles were used to find general cancer, regional cancer and specific cancer biomarkers that can be used for cancer detection, classification and treatment monitoring.

  Study EGAS50000000417

• New England-Based Case-Control Study of Ovarian Cancer

  The case-control data provided to dbGaP were collected under NCI grant number CA54419 which had 3 enrollment phases: I (1992-1997), II (1998-2002) and III (2003-2008). Altogether, CA54419 funded 15 years of data and specimen collection, resulting in one of the longest running population based case-control studies of ovarian cancer. The study goal was to examine reproductive factors, lifestyle exposures, and genetic background in relation to ovarian cancer risk. The project recruited cases from Eastern Massachusetts and New Hampshire, and became known as the New England-based Case-Control study (NECC) of ovarian cancer. 3957 ovarian cancer cases diagnosed at ages 18-80 and residing in Eastern Massachusetts and New Hampshire were identified through tumor boards and registries. Of these, 3083 (78%) were eligible and among those eligible, 2203 (71%) were enrolled. After excluding 127 non-epithelial and 35 mixed mesodermal tumors, 2041 cases with epithelial tumors of ovarian, primary peritoneal, and fallopian tube origin, including borderline malignancies were included. On average, cases were interviewed 10 months after their diagnosis. A pathologist reviewed pathology reports and recorded histologic subtype, grade, and stage. Mixed ovarian cancers described as predominantly one type were classified as that type. Undifferentiated, transitional cell tumors, or mixed serous/transitional cell tumors were counted as serous. Other mixed epithelial, malignant Brenner, and unspecified epithelial tumors were classified as other. 2100 controls were identified through random digit dialing (RDD), driver-license lists, and town-resident lists. During the first funding phase from 1992 to 1997, 420 (72%) controls identified through RDD and 102 (51%) through town-resident lists agreed to participate. From 1998 to 2008, only town-resident lists were used to identify potential controls. 4366 controls were identified, of whom 1426 (33%) were ineligible if they had died, moved, or were seriously ill or if they did not have a working telephone, speak English, or have at least one ovary. Of eligible controls, 1362 (46%) declined to participate by phone or via 'opt-out' postcard and 1578 (54%) were enrolled. Controls were frequency matched to cases by 5-year age groups and region of residence. In all phases, after written informed consent, demographic information, reproductive and medical history, and habits were assessed by in-person or telephone interview (in a few instances). All of the questions were framed with respect to a reference date defined as 1 year before the diagnosis date for women in the case group and the date of interview for those in the control group. This study was approved by institutional review boards at Dana Farber Harvard Cancer Center and Dartmouth Medical Center.

  Study phs001034

• Liquid Biopsy Detection of Tumor-specific Structural Variants in High Grade Serous Ovarian Cancer

  WGS Liquid Biopsy. Recurrence is frequent for most patients with high grade serous ovarian cancer (HGSOC), even after effective chemotherapy induced remission. However, after achievement of complete clinical response, the minimal residual disease is often insufficient for genomic analysis. Therefore, methods to interrogate the clonal composition and molecular properties of minimal residual disease are needed to better understand the mechanisms of HGSOC relapse. To address this unmet need, we developed and validated a novel cfDNA-based approach for tracking disease burden using NGS-informed tumor specific structural variants (SVs). Methods: The optimization of the methodology was first performed using synthetic cfDNA generated by ultrasonication of gDNA from ovarian cancer cell lines. Following the optimized workflow, whole genome sequencing of multisite biopsies from pre-treatment HGSOC patients were performed and high confidence SVs were called by consensus of multiple published SV callers. Real-time PCR and digital droplet PCR (ddPCR) were used for assays development.

  Study EGAS50000001044

• Combined gene expression and digital pathology identifies molecular mediators of T cell exclusion and immune suppression in ovarian cancer

  Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what determines the spatial distribution of T cells in the tumour microenvironment is not well understood. Coupling digital pathology and transcriptome analysis on a large ovarian tumour cohort, we develop a machine learning approach to molecularly classify and characterize tumour-immune phenotypes. Our study identifies two important hallmarks characterizing T cell excluded tumours: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFb and activated stroma. Furthermore, we identify TGFb as a key mediator of T cell exclusion. TGFb reduces MHC-I expression in ovarian cancer cells in vitro; TGFb also activates fibroblasts and induced extracellular matrix (ECM) production as a potential physical barrier to hinder T cell infiltration. Our findings indicate that targeting TGFb may represent a promising strategy to overcome T cell exclusion and improve clinical benefits of cancer immunotherapy.

  Study EGAS00001003487

• Comprehensive molecular profiling for breast cancer patients and high-risk individuals.

  Although germ-line mutations in BRCA1 and BRCA2 gene are responsible for familial breast and ovarian cancer, the detailed mechanism of tumorigenesis is yet unknown. Here, we performed next-generation sequencing to determine the genomic profiles of familial breast cancer tumorigenesis. Target-capture sequencing of fresh-frozen or formalin-fixed-paraffin-embedded (FFPE) samples of breast cancer or normal breast tissue were performed.

  Study JGAS000368

• Single-cell RNA sequencing of human omental tissue in benign and metastatic ovarian cancer

  To elucidate the cellular and molecular mechanisms underlying omental homeostasis and its transformation during ovarian cancer metastasis, a human omental cell atlas was generated encompassing both benign and metastatic conditions. Single-cell RNA sequencing was performed on freshly dissociated omental tissue samples from patients with newly diagnosed benign and malignant disease. Samples collected during diagnostic surgery covered distinct anatomical regions, enabling comparison between non-metastasized omentum and sites along the metastatic gradient, including distant, peritumoral, and tumor core areas.

  Study EGAS50000001465

• Comprehensive molecular profiling of high-grade serous ovarian cancer

  The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC) is not well understood. Here, we performed comprehensive molecular analysis, including high-pass whole genome sequencing, targeted deep sequencing, RNA sequencing, reverse phase protein arrays and immune assessment, on primary and metastatic sites from highly clinically annotated HGSC samples. Samples were obtained pre-treatment based on a laparoscopic triage algorithm from patients who underwent R0 tumor debulking, or received neoadjuvant chemotherapy (NACT) with excellent or poor response.

  Study EGAS00001003804

• Identification of genomic aberrations in low-grade serous ovarian cancer

  Low-grade serous ovarian cancer (LGSOC) is a rare disease that occurs more frequently in younger women compared with high-grade disease. The current treatment is suboptimal, and better understanding of molecular pathogenesis of this disease is needed. In this study, we compared the whole genome sequences of LGSOCs from short-term and long-term survivors (defined as <40 and >60 months, respectively). Our goal was to identify novel genomic aberrations in LGSOC, especially in short-term survivors.

  Study EGAS00001006679

• molecular profiles of serum-derived extracellular vesicles in high-grade serous ovarian cancer

  Patients with high-grade serous ovarian cancer (HGSC) who have no visible residual disease (R0) after primary surgery have the best clinical outcomes, followed by patients who undergo neoadjuvant chemotherapy (NACT) and have response enabling interval cytoreductive surgery. Clinically useful predictive biomarkers for such distinctions are still lacking. Extracellular vesicles (EVs) have been recognized as liquid biopsy-based biomarkers for early cancer detection and disease surveillance in other disease settings. In this study, we performed extensive molecular characterization of serum-derived EVs and correlated them with therapeutic outcomes in patients with HGSC.

  Study EGAS00001006350

• The DNA methylome of cervical cells and risk of ovarian cancer

  Study EGAS00001005045

• Longitudinal single-cell RNA-seq data of metastatic ovarian cancer

  Study EGAS00001005010

• Methylation data for Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  Study EGAS00001008175

• Long-Read Sequencing to Identify Inherited Mutations Predisposing to Breast Cancer

  We aimed to detect deeply intronic mutations within genes linked to breast/ovarian cancer that are potentially under-reported in clinical testing due to technical limitations. Current DNA and RNA tests typically exclude these regions, which harbor many variants within complex repetitive sequences that short-read sequencing cannot align. By employing targeted long read sequencing together with recent in silico prediction tools, we assessed the implications of rare deep intronic variants in severely affected patients with breast, ovarian, and/or metastatic prostate cancer, who had previously tested negative using standard genomic or cDNA methods. Through this approach, we identified participants who carried deep intronic mutations in tumor suppressor genes, resulting in abnormal transcripts causing premature truncations and loss of gene function. This study underscores the potential of long read DNA and cDNA sequencing in enhancing mutation discovery efforts.

  Study phs003638

• The Ovarian Cancer Association Consortium OncoArray genome-wide association study

  A custom Illumina genotyping array, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis as described in PMID:27697780.The array was used to genotype ovarian cancer cases and controls from multiple studies participating in the Ovarian Cancer Association Consortium, of which 54,747 passes QC.An initial principal components analysis was carried out using a method described in PMID:27697780 to assign subject to intercontinental ancestry groups: “European”, “African”, “Asian” and "Other". Within ancestry principal components analysis was carried using a set of ~33k unlinked markers. Subsequent analyses were adjusted for the ancestry specific PCs: 9 Eur, 10 Asian, 1 African and 6 Mixed. These PCs are included in the imputed dataset phenotypes file

  Study EGAS00001002305

• Transcriptome Sequencing Data of High Grade Serous Ovarian Cancer

  Study EGAS00001004714

• Identification of responsible genes and development of standardized medicine for familial breast cancer by genetic analysis with NGS technology

  Aims: To clarify risk of germline variants of known causal genes for Hereditary Breast Ovarian Cancer Syndrome in Japan by combinatorial analysis of somatic and germline variants in the breast cancer tissue. Methods: Target caputure analysis by using Illumina HiSeq 2000; the panel genes are 119 genes including 30 HBOC known causal genes. Participants/Materials: 108 whole blood and 124 primary tumor samples from familial breast cancer patients.

  Study JGAS000224

• Matched_Ovarian_Cancer_Sequencing

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from 15 ovarian cancer samples and subjected to total of eight lanes of 37 bp, paired end sequencing on the llumina GA. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000155

• Human pan-cancer plasma cfRNA study - raw data

  This study contains mRNA capture sequencing data from plasma of 266 different human donors. The first, pan-cancer, cohort covers 25 high-grade to metastatic cancer types (8 cancer patients per type) and a control group (8 healthy donors). The validation cohort comprises additional plasma samples from ovarian, prostate and uterine cancer patients (12 per type) as well as additional samples from controls (22 new and 8 repeated). Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Study EGAS00001006755

• SCANDARE MACARON

  Among gynecological cancers, high-grade serous ovarian cancer has the highest prevalence and more than 75% of patients have advanced stage at diagnosis with a 5-year survival of 40%. When the initial complete surgical removal is not possible (60% of patients), an interval surgery can be considered after three to four cycles of neoadjuvant chemotherapy to reduce the tumor mass. However, in approximately 50% of cases the tumor has little or no response to neoadjuvant chemotherapy. Therefore, identification of potential drug targets, biomarkers and/or pathways whose modulation can help in the prevention, interception, or curing of the disease is essential to address the unmet need. Therefore, MACARON project aims to address these issues through the identification of shared neoantigens arising out of somatic alterations and aberrant transcriptional programs in ovarian cancer DNA/RNA datasets.

  Study EGAS50000000145