Project description:Ovarian cancer (OC) is the most lethal gynecologic malignancy, attributed by late diagnosis. Genetic alteration of BRCA1/2 was well known risk factors in people who does not occur ovarian cancer. There is a need for convenient and continuous diagnosis of ovarian cancer after genetic testing, and we intend to apply a blood biomarker-based liquid biopsy. In a retrospective study, 20 OC patients and 20 normal controls were used for plasma samples, and BRCA1/2 carriers accounted for half in each group. We applied the bottom-up proteomics approach to depleted plasma samples with a nano-flow LC-MS and analyzed protein data quantitatively.
Project description:The ataxia telangiectasia-mutated (ATM) gene is a moderate-risk breast cancer susceptibility gene; germline loss-of-function variants are found in up to 3% of hereditary breast and ovarian cancer (HBOC) families who undergo genetic testing. So far, no clear molecular features of breast tumors occuring in ATM deleterious variant carriers have been described, but identification of an ATM-associated tumors signature may help patients' management. To characterize hallmarks of ATM-associated tumors, absolute copy number variation and loss of heterozygosity profiles were obtained from the OncoScan SNP array.
Project description:Ovarian cancer has a high mortality rate due, in part, to the lack of early detection and incomplete understanding of the origin of the disease. The hen is the only spontaneous model of ovarian cancer, and can therefore aid in the identification and testing of early detection strategies and therapeutics. To our knowledge, no studies to date have examined global gene expression in ovarian cancer of the hen. Our aim was to combine the use of the hen animal model and microarray technology to identify differentially expressed genes in ovarian tissue from normal hens compared to hens with ovarian cancer.
Project description:Heredity is a major risk factor for ovarian cancer, but many families escape detection. Refined diagnosis of ovarian cancers linked to the breast and ovarian cancer (HBOC) syndrome and the hereditary nonpolyposis colorectal cancer (HNPCC) syndrome would allow cancer prevention in high risk families. In order to delineate genetic profiles of hereditary ovarian cancer, we applied genome wide array comparative genomic hybridization to 24 sporadic tumors, 12 HBOC associated tumors (BRCA1 mutations) and eight HNPCC associated tumors (mismatch repair gene mutations). Unsupervised cluster analysis identified two distinctive clusters related to genetic complexity. Most sporadic and HBOC associated tumors had complex genetic profiles with multiple gains and losses with an average of 41% of the genome altered, whereas mismatch repair defective tumors had stable genetic profiles, with an average of 18% of the genome altered. Losses of 4q34, 13q12-q32 and 19p13 were overrepresented in the HBOC subset, gains of chromosomes 17 and 19 characterized the HNPCC tumors and gains of 20q11 were more common in the sporadic tumors. The genetic distinction between HBOC and HNPCC associated ovarian cancer suggests that genetic profiles can be applied for refined classification of hereditary cases and reflects tumor development along different genetic pathways.
Project description:Background and study aims
Patients who are diagnosed with womb, bowel, or ovarian cancer that fulfill NHS genetic testing criteria are recommended to have genetic testing to see if their cancer was related to an inherited gene alteration. Identifying carriers of alterations allows novel personalised cancer treatments, prevention of second cancers, and testing of family members for cancer screening and prevention. Genetic testing requires pre-test counselling to ensure patients are informed about the impact of having a genetic test and managing the result. This ‘genetic counselling’ has traditionally been provided by genetics services. However, it is now routinely being offered by cancer-treating teams in an approach called “mainstreaming”. Currently, the demand for genetic counselling and testing is swiftly increasing and capacity constraints requires the development of new scalable cost and resource-efficient implementation models. This study will assess if pre-test counselling and genetic testing can be done using a direct-to-patient model. Participants will receive genetic testing information on a smartphone app or website that they can access at home along with counselling support through a study telephone helpline. Those who agree to testing can consent via the app and perform testing at home with a saliva genetic testing kit delivered and returned by post. In the study this direct-to-patient approach is directly compared to the standard mainstreaming approach.
Who can participate?
Patients aged 18 years and over diagnosed with bowel, womb, or ovarian cancer who are eligible for NHS genetic testing
What does the study involve?
This study compares and evaluates the uptake of genetic testing using both approaches. The researchers also assess patient satisfaction, quality-of-life, and psychological outcomes following testing, using standardized or customized questionnaires over 1 year of follow-up. Clinician opinions will be elicited. Some patients will also be interviewed to assess attitudes, experiences, and impact on emotional wellbeing. An economic analysis will be undertaken to assess the cost-effectiveness of this approach for the NHS.
Project description:Identifying germline BRCA1/2 mutation carriers is vital for reducing their risk of breast and ovarian cancer; however, many carriers are not referred for genetic testing. While population-wide testing is not feasible, a cheap functional screen for phenotypic ‘BRCAness’ could guide efforts for focused genetic counseling and improve cancer prevention and early detection. The aim of this study was to derive a serum-based miRNA panel to identify BRCA1/2 mutation carriers among healthy controls. We performed a diagnostic biomarker study based on serum samples collected between by six international cohorts. Serum samples from 653 healthy women with known mutation status of BRCA1 and BRCA2 were used in the analysis. All individuals had no history of prior cancer or any detected malignancies for at least 12 months after sample collection. Among the study population, 350 (53.6%) subjects had BRCA mutations and 303 (46.4%) were BRCA1/2 – wild-type. In all individuals, we isolated and quantified miRNAs expression using RNA-sequencing. Variable selection based on differential expression analysis on merged, batch adjusted cohorts was performed to identify a set of miRNAs associated with BRCA mutation carrier status.
Project description:Ovarian cancer has a high mortality rate due, in part, to the lack of early detection and incomplete understanding of the origin of the disease. The hen is the only spontaneous model of ovarian cancer, and can therefore aid in the identification and testing of early detection strategies and therapeutics. To our knowledge, no studies to date have examined global gene expression in ovarian cancer of the hen. Our aim was to combine the use of the hen animal model and microarray technology to identify differentially expressed genes in ovarian tissue from normal hens compared to hens with ovarian cancer. Ovarian tissue samples from whole ovaries were collected from hens for RNA extraction and hybridization on Affymetrix microarrays. Hens were matched for age and laying status. Normal hens (n=3) showed no gross or histopathological evidence of ovarian cancer, while cancer specimens (n=3) had tumors that were stage 2 (restricted to the ovary and observable at necropsy) or 3 (ovarian tumor with abdominal seeding). Total RNA was extracted using TRIZOL according to the manufacturer's instructions.
Project description:The hallmark of human cancer is heterogeneity, mirroring the complexity of genetic and epigenetic alterations acquired during oncogenesis. We extracted DNA of 14 cultured human ovarian carcinoma cell lines subjected to pooled shRNA screen using TRC 1.0 library, and performed DNAseq. 14 ovarian carcinoma cell lines DNAseq data.