3288 results for "ovarian cancer"

in 14.60 milliseconds.

• 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

• Complete Genomics paired end sequencing; Ovarian cancer

  We sequenced the genomes from a monozygotic twin discordant for schizophrenia and a tumor-normal pair of an ovarian cancer patient. Using whole-genome twin data to discriminate between correctly identified single nucleotide variants (SNVs) and errors a strategy for the accurate detection of SNVs was developed. By applying stringent sequencing quality measures, excluding error-prone regions and selecting SNVs identified by different mapping and variation calling algorithms, error rates were ~37-fold reduced. This enabled us to identify the first discordant SNVs in monozygotic twins using whole-genome sequencing. In addition, by showing that novel SNVs are highly enriched in errors, accurate estimates of the number of novel and rare SNVs occurring in unrelated Caucasian individuals were obtained. Finally, somatic mutations in coding and regulatory sequences were reliably identified in the highly rearranged ovarian tumor. Overall, our data demonstrate that strategies to reduce error rates in whole-genomes are required for disease gene discovery.

  Study EGAS00001000158

• Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) - OncoArray Genotypes

  The data come from 40 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). CIMBA recruits individuals with pathogenic mutations in BRCA1 or BRCA2. The majority of carriers were recruited through cancer genetics clinics offering genetic testing, and were enrolled into national or regional studies. The remainder were identified by population-based sampling of cases, or community recruitment. Eligibility to participate is restricted to carriers of pathogenic BRCA1/2 mutations who were 18 years or older at recruitment. Information collected included amongst other variables: age at recruitment; ages at breast and ovarian cancer diagnosis; and estrogen receptor (ER) status. Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in Phelan et al, Identification of twelve new susceptibility loci for different histotypes of epithelial ovarian cancer, Nat Genet. 2017 May;49(5):680-691 (PMID:28346442), and Milne et al, Identification of ten variants associated with risk of estrogen receptor negative breast cancer, Nat Genet (in press).

  Study phs001321

• Spatial and temporal intra-tumoural heterogeneity in advanced High-Grade Serous Ovarian Cancer: implications for surgical and clinical outcomes

  Limited evidence exists on the extent and impact of spatial and temporal heterogeneity of high grade serous ovarian cancer (HGSOC) on tumour evolution and patients surgical and clinical outcome. We investigated this through systematic mapping of multi-site tumours at initial presentation and matched relapse from 49 chemo-naïve HGSOC patients with high tumour load, operated upfront. Our data provides a unique insight into the tumour evolution and metastatic pathways of HGSOC across time and space, how this complexity relates to surgical and clinical outcome and its consequences on clinical decision-making.

  Study EGAS00001007164

• BRCA1 secondary splice-site mutations

  BRCA1 splice isoforms d11 and d11q can contribute to PARP inhibitor (PARPi) resistance by splicing-out mutation-containing exons, producing truncated, partially-functional proteins. However, the clinical impact and underlying drivers of BRCA1 exon skipping remain undetermined. We analyzed nine ovarian and breast cancer patient derived xenografts (PDX) with BRCA1 exon 11 frameshift mutations for splice isoform expression and therapy response.

  Study EGAS50000000022

• Cancer Genetic Markers of Susceptibility (CGEMS) Prostate Cancer Genome-Wide Association Study (GWAS) - Primary Scan (Stage 1) - PLCO Screening Trial

  The Cancer Genetic Markers of Susceptibility (CGEMS) prostate cancer genome-wide association study (GWAS) included genotyping approximately 550,000 SNPs (Phase 1A with HumanHap300 and Phase 1B HumanHap240, both from Illumina, San Diego, CA) in 1,172 prostate cancer patients and 1,157 controls of European ancestry from the Prostate, Lung, Colon and Ovarian (PLCO, http://www.cancer.gov/prevention/plco/) Cancer Screening Trial. The original analysis published in Nature Genetics [PMID: 17401363] included 2,282 subjects. After improvement and revisions of the original analysis, 2,252 subjects were submitted to dbGaP.

  Study phs000207

• PDX gene expression

  Investigation of the anti-tumor activity of the potent, highly selective, orally bioavailable CHK1 inhibitor (CHK1i), SRA737, in both acquired PARPi-resistant BRCA1/2 mutant and CCNE1amp high-grade serous ovarian cancer (HGSOC) models. We analyzed gene expression in five patient derived xenografts (PDX) that responded to CHK1i and three PDX that had a poor response to CHK1i.

  Study EGAS50000000084

• Gene Expression of Small Cell Carcinoma of the Ovary-Hypercalcemic Type (SCCOHT)

  Small cell carcinoma of the ovary-hypercalcemic type (SCCOHT) is a rare and aggressive form of ovarian cancer afflicting young women at a median age of 24 years. SCCOHTs are characterized by loss of protein expression of SWI/SNF chromatin remodeling ATPases SMARCA4 and SMARCA2 through mutation and epigenetic silencing, respectively. This study aims to establish gene expression profiles of this cancer through RNA-Seq of fourteen pathologically confirmed cases of SCCOHT tumors.

  Study phs001528

• Germline DNA Methylation Associated with Breast Cancer Predisposition

  Understanding and explaining hereditary predisposition to cancer has focused on the genetic etiology of the disease. However, mutations in known genes associated with breast cancer such as BRCA1 and BRCA2 account for less than 25% of familial cases of breast cancer. Heritable epigenetic modifications, in the form of hypermethylated MLH1 promoter alleles, have recently been shown to promote hereditary nonpolyposis colorectal cancer. We investigated the potential for an epigenetic basis for hereditary breast cancer by performing deep bisulfite sequencing of CpG islands and known promoter regions in germline DNA from 100 familial or early-onset breast or ovarian cancer patients.

  Study phs001699

• Evolution of Core Archetypal Phenotypes in High-Grade Serous Ovarian Cancer (HGSOC)

  The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells in response to chemotherapy is only partially understood. To uncover phenotypic changes associated with chemotherapy resistance, we performed single-cell RNA-sequencing (scRNA-seq) or whole-genome sequencing of 23 total patients, with longitudinal samples collected from 9, treatment-naïve samples from 8 patients, and post-treatment samples from 6 patients. Our study revealed that the HGSOC transcriptome could be described using three core archetypal phenotypes, defined as oncogenic tasks that describe majority of the transcriptional data. We implemented a multi-task learning approach to identify the biological tasks of each archetype and identified metabolism and proliferation, cellular defense response, and DNA repair signaling. The “metabolism and proliferation” archetype evolved during treatment and was enriched in cancer cells from patients that received multiple-lines of treatment and had elevated tumor burden indicated by CA-125 levels. The emergence of archetypes was not consistently linked to specific whole-genome driver mutations. However, archetypes were closely associated with sub-clonal clusters at the single-cell level, indicating that cancer cell sub-populations specialize in particular biological tasks. Our study reveals a defining principle of ovarian tumor evolution using temporal scRNA-seq profiles, identifies the key phenotypic features across patients and links metabolic shifts with a response to chemotherapy.

  Study phs002294

• Ovarian cancer organoid biobank

  Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Study EGAS00001003073

• ARID1A Mutations in Endometriosis-Associated Ovarian Carcinomas

  We have sequenced the whole transcriptomes of 18 ovarian clear-cell carcinomas and 1 ovarian clear-cell carcinoma cell line and found somatic mutations in ARID1A (the AT-rich interactive domain 1A [SWI-like] gene) in 6 of the samples. ARID1A encodes BAF250a, a key component of the SWI–SNF chromatin remodeling complex. We sequenced ARID1A in an additional 210 ovarian carcinomas and a second ovarian clear-cell carcinoma cell line and measured BAF250a expression by means of immunohistochemical analysis in an additional 455 ovarian carcinomas

  Study EGAS00000000075

• Project for Development of Innovative Research on Cancer Therapeutics; Identifiying the predictive factors for response to chemoherapy in ovarian cancer

  To identify novel predictive biomarkers of response to chemotherapy for clear cell carcinoma of the ovary

  Study JGAS000076

• Genome Instability in Mammary Cells of Pathogenic BRCA1/2 Mutation Carriers

  It remains unknown if inherited germline mutations in the BRCA1 or BRCA2 gene increase the risk of breast and ovarian cancer by elevating mutation rate in mammary cells. Here we show, using a single-cell whole genome sequencing approach, that mammary luminal epithelial cells isolated from tissues obtained from preventive mastectomy surgeries in women with a pathogenic BRCA1/2 germline mutation, exhibit a statistically significant, increased mutation frequency as compared to age-matched controls without genetic risk of breast cancer.

  Study phs002411

• Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

  Study phs000892

• Single cell RNA sequencing and Whole Genome Sequencing on different cells from the same sample for a triple negative patient derived xenograft and ovarian cancer cell lines.

  Measuring gene expression of genomically defined tumour clones at single cell resolution would associate functional consequences to somatic alterations, as a prelude to elucidating pathways driving cell population growth, resistance and relapse. In the absence of scalable methods to simultaneously assay DNA and RNA from the same single cell, independent sampling of cell populations for parallel measurement of single cell DNA and single cell RNA must be computationally mapped for genome-transcriptome association. Here we present clonealign, a robust statistical framework to assign gene expression states to cancer clones using single-cell RNA-seq and DNA-seq independently sampled from an heterogeneous cancer cell population. We apply clonealign to triple-negative breast cancer patient derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either DNA-Seq or RNA-Seq alone.

  Study EGAS00001003387

• The evolution of ovarian high grade serous carcinoma from STIC lesions

  We performed Ampliseq on 11 samples on a targeted panel of 17 genes.

  Study EGAS50000000361

• Female Infertility: Primary Ovarian Insufficiency

  Premature ovarian failure, or primary ovarian insufficiency (POI) is a phenotype of diminished or absent ovarian function occurring in 1-2% of reproductive aged women. Most cases occur spontaneously. Evaluation of the gametes in women with POI is difficult and invasive. Practitioners must often rely on indirect biomarkers of ovarian function and oocyte health, making it difficult to identify patients who may benefit from therapies allowing them to achieve pregnancy utilizing their own oocytes. This study will generate exome sequences from POI patients in an effort to elucidate the causes of unexplained POI and to better understand the normal processes of ovarian aging. A better understanding of the genetics of ovarian function may lead to new non-invasive tools for managing women's reproductive health, and direct better use of existing biomarkers in diagnosis, screening and predicting clinical outcomes.

  Study phs001174

• Transcriptional profiling of ovarian tumours and cell lines

  Purpose: Endogenous retroviruses (ERVs) play a role in a variety of biological processes, including embryogenesis and cancer. DNA methyltransferase inhibitors (DNMTi)-induced ERV expression triggers interferon responses in ovarian cancer cells via the viral sensing machinery. Baseline expression of ERVs also occurs in cancer cells, though this process is poorly understood and previously unexplored in epithelial ovarian cancer (EOC). Here, the prognostic and immunomodulatory consequences of baseline ERV expression was assessed in EOC. Experimental Design: ERV expression was assessed using EOC transcriptional data from TCGA and from an independent cohort (HH), as well as from untreated or DNMTi-treated EOC cell lines. LASSO logistic regression defined an ERV expression score to predict patient prognosis. Immunohistochemistry (IHC) was conducted on the HH cohort. Combination of DNMTi treatment with γδ T cells was tested in vitro, using EOC cell lines and patient-derived tumor cells. Results: ERV expression was found to define clinically relevant subsets of EOC patients. An ERV prognostic score was successfully generated in TCGA and validated in the independent cohort. In EOC patients from this cohort, a high ERV score was associated with better survival (log-rank p=0.0009) and correlated with infiltration of CD8+PD1+ T cells (r=0.46, p=0.0001). In vitro, baseline ERV expression dictates the level of ERV induction in response to DNMTi. Manipulation of ERV expression by DNMTi resulted in improved EOC cell killing by cytotoxic immune cells. Conclusions: These findings uncover the potential for baseline ERV expression to robustly inform EOC patient prognosis, influence tumor immune infiltration and affect anti-tumor immunity.

  Study EGAS00001004814

• Genomic analysis of HGSOC using long read sequencing

  High-grade serous ovarian cancer (HGSOC) is characterized by widespread genomic instability, but genomic and epigenomic alterations within repetitive regions remain poorly understood. This study aims to investigate genomic and epigenomic variations in HGSOC using Oxford Nanopore long-read sequencing technology. High-molecular-weight DNA was extracted from cryopreserved, pre-treatment tumor samples and matched blood specimens. The objectives include developing a robust long-read sequencing analysis pipeline, identifying novel genomic and epigenomic variations, and exploring potential applications in future clinical and basic research.

  Study EGAS50000001036

• Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness

  RNAseq from patient-derived primary tumor cells, cultured or not on organotypic cultures mimicking the tumor microenvironment

  Study EGAS50000000355

• Linked Read Sequencing of Gastric Cancer Metastases for Complex SV Resolution

  In this study, linked read sequencing was performed on two ovarian metastases and matched normal tissue, from a patient with primary diffuse gastric cancer. Linked read sequencing is a DNA preparation technology whereby high molecular weight molecules of DNA are uniquely barcoded prior to fragmentation and sequencing, thus retaining information about genomic contiguity. This study performed an extended analysis of linked read sequencing data to resolve the complex structures of structural variants in the cancer genomes. Complex structural rearrangements were identified in the genomic region surrounding the known oncogene FGFR2, and the association between FGFR2 and gastric cancer metastasis was demonstrated in an organoid model.

  Study phs001362

• sWGS of Pap test smears from healthy donors and HGSOC patients and matched tumor tissue

  Shallow whole genome sequencing was performed on Pap test smears considering at least 10 M reads per sample. The cohort consists of 77 samples from healthy women, i.e. no tumor diagnosis, and 65 samples from women with a diagnosis of high-grade serous ovarian cancer (HGSOC) taken months or years before diagnosis. 44 primary tumor samples matched to the respective HGSOC patients were sequenced in the same manner as the Pap test smears.

  Study EGAS00001007084

• Reduced Representation Bisulfite Sequencing (RRBS) in various tissues to discover DNA methylation markers for the diagnosis of breast and ovarian cancer.

  Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. In addition, monitoring treatment and early detection of fatal breast cancer (BC) remains a major unmet need. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence.In order to discover the most relevant CpG regions, we used RRBS and analysed several tissue samples: 11 prospectively collected invasive epithelial ovarian cancer samples (high grade serous n=8, low grade serous n=1, endometrioid n=1, mucinous n=1, mean age = 54.7 years), 8 prospectively collected invasive ductal breast cancer samples (2/8 triple negative; mean age = 56.6 years), one benign tumor (papillary serous cystadenoma, age = 86 years), 18 non-neoplastic tissue samples (breast n=7 and adnexal n=11, mean age = 60.2 years), two non-neoplastic endometrial tissues (mean age = 68 years) and twenty three white blood cell samples (mean age = 57.8 years) were assessed by RRBS. Genome wide methylation analysis was performed by Reduced Representation Bisulfite Sequencing (RRBS) at GATC Biotech. DNA was digested with MspI followed by size selection of the library, providing enhanced coverage for the CpG-rich regions. The digested DNA was adapter ligated, bisulfite modified and PCR amplified. The libraries were sequenced on Illumina’s HiSeq 2500. Analysis of the first samples sequenced with 100bp paired-end mode showed that the library insert size was small. Therefore, the remaining samples were sequenced with 50 bp paired-end mode. Using Genedata Expressionist® for Genomic Profiling v9.1, we established a bioinformatics pipeline for the detection of cancer specific differentially methylated regions (DMRs). The most promising DMRs were taken forward for the development and validation of serum based clinical assays.

  Study EGAS00001002609

• Tumor microenvironment study of ovarian granulosa cell tumors

  Adult-type granulosa cell tumors (aGCT) are rare ovarian sex cord tumors with few 41 effective treatments for recurrent disease. The objective of this study was to compare global gene expression profiles and characterize the tumor microenvironment (TME) of primary and recurrent aGCTs in order to identify correlates of disease recurrence. Total RNA sequencing was performed on 24 pathologically confirmed, cryopreserved aGCT samples, including 8 primary and 16 recurrent tumors. A total of 31 differentially expressed genes were identified between primary and recurrent aGCT. TME analysis demonstrated significantly higher fractions of neutrophils and macrophages in recurrent tumors in conjunction with significantly lower fractions of cancer-associated fibroblasts and endothelial cells.

  Study EGAS00001006478

• Genomic profiling of ovarian adult type granulosa cell tumors

  To investigate the genomic landscape of primary and recurrent ovarian adult type granulosa cell tumors, we first identified an exploratory cohort comprised of cryopreserved surgical biopsies from 24 patients (primary, n = 8; recurrent, n = 16) with 20 having matched normal tissue or peripheral blood samples. We performed whole exome sequencing (WES) on these tumor samples at 200X target coverage (mean 226; range 165-296) and also performed WES on the available normal samples. In addition, we performed cancer gene panel sequencing using the T200.1 hybrid capture platform on FFPE tissue from 55 additional patients (primary, n = 27; recurrent, n = 28), of which we sequenced matched normal tissue for a total of 44.

  Study EGAS00001002833