Browse
Submit Data
Databases
API
Help

Dataset Information

4 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Screening for Gynecologic Cancers in Hereditary Nonpolyposis Colorectal Cancer (HNPCC) Patients

ABSTRACT: Among women with HNPCC, this study will assess: 1. Knowledge of screening recommendations for endometrial and ovarian cancers. 2. Perceived risk and cancer worries regarding endometrial, ovarian and colorectal cancers. 3. Adherence to screening recommendations for endometrial, ovarian and colon cancers. 4. Perceived benefits,supports and barriers to endometrial and ovarian cancer screening. 5. Patterns of communication about endometrial and ovarian cancer risk within families with HNPCC and with health care providers. 6. Patient preferences for potential cancer screening and cancer prevention strategies related to HNPCC-associated cancers.

DISEASE(S): Colon Cancer,Colonic Neoplasms

PROVIDER: 2042655 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Json Xml

Similar Datasets

Genomic profiling of hereditary epithelial ovarian cancer using tiling resolution array CGH

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.

2011-04-27 | GSE28850 | GEO

Transcription profile of colon biopsies from normal (NOR) donors, patients, underwent resection for CRC (M-CRC) and patients carriers of mutations predisposed to HNPCC (HNPC)

Project description:The challenge of preventing colorectal cancer (CRC) is the early identification of individuals whose apparently normal colorectal mucosa will develop cancer, because of inherited trait or environmental exposure. We sought to use genome-wide expression profiling of endoscopic biopsies to detect a signature of propensity for cancer. We performed oligonucleotide microarray analysis of normal appearing mucosa of the following cases: healthy individuals, disease-free carriers predisposed to HNPCC (hereditary non-polyposis CRC), disease-free patients who underwent curative large bowel resection for CRC 1 to 15 years earlier and patients with CRC. This profiling is based on the analysis of 4 donors who underwent curative large bowel resection for CRC from 1 to 19 years before (M-CRC samples), 4 disease-free carriers of mutations in the mismatch repair system genes, who are predisposed to develop HNPCC (HNPCC samples) and 4 endoscopy-negative, asymptomatic individuals (NOR samples)

2013-11-30 | E-GEOD-23011 | biostudies-arrayexpress

Cross-cancer genome-wide association study of endometrial cancer and epithelial ovarian cancer identifies genetic risk regions associated with risk of both cancers

Project description:Accumulating evidence suggests a relationship between endometrial cancer and epithelial ovarian cancer. For example, endometrial cancer and epithelial ovarian cancer share epidemiological risk factors and molecular features observed across histotypes are held in common (e.g. serous, endometrioid and clear cell). Independent genome-wide association studies (GWAS) for endometrial cancer and epithelial ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. Using GWAS summary statistics, we explored the shared genetic etiology between endometrial cancer and epithelial ovarian cancer. Genetic correlation analysis using LD Score regression revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e. inverse-variance meta-analysis, co-localization, and M-values), and performed analyses by stratified by subtype. We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10-9). In addition, four novel regions at 7p22.2, 7q22.1, 9p12 and 11q13.3 were identified at a sub-genome wide threshold (P < 5 × 10-7). Integration with promoter-associated HiChIP chromatin loops from immortalized endometrium and epithelial ovarian cell lines, and expression quantitative trait loci (eQTL) data highlighted candidate target genes for further investigation.

2020-07-30 | GSE155328 | GEO

HNPCC-Sys: Molecular Characterization of Lynch Syndromes

Project description:HNPCC-Sys: Molecular Characterization of Lynch Syndromes

| PRJNA393750 | ENA

Transcription profile of colon biopsies from normal (NOR) donors, patients, underwent resection for CRC (M-CRC) and patients carriers of mutations predisposed to HNPCC (HNPC)

2013-11-30 | GSE23011 | GEO

OCaMIR a non-invasive early diagnostic test for ovarian cancer: A multi-cohort retrospective and prospective analysis

Project description:Owing to the lack of effective screening tools and early detection biomarkers, ovarian cancer (OC) still remains as a deadly disease with highest mortality among other gynecological cancers. So far there have been no attempts to discover biomarkers using early stage OC patients. MicroRNAs (miRNAs) have been recognized as great tool to develop non-invasive biomarkers in various cancers including ovarian cancer.

2020-03-06 | GSE127873 | GEO

Comparison to Psychological, Medical and Emotional Influencing Communication and Achievement Factors to Oncogenetics Tests

Project description:The purpose of the study was to analyze the psychological and emotional determinants of domestic dissemination of information about genetic risk of cancer and to compare the level of diffusion syndromes in breast/ ovarian cancer ( BRCA1 / BRCA2) and colon/endometrial ( HNPCC )

| 2300891 | ecrin-mdr-crc

Transcriptomic analyses of high-grade neuroendocrine carcinoma of gynecologic origin

Project description:High-grade neuroendocrine carcinomas (NECs) of the cervix are rare, aggressive cancers accounting for about 1-1.5% of all cervical cancer. The 5-year survival is up to 36% for early-stage disease; however, the advanced-stage disease has <10% survival, with relapse rates exceeding 90%. These cancers are likely to have a vascular invasion and nodal or visceral metastasis. Unfortunately, NEC of the cervix affects young women with a median age of 37. High-grade NECs of other gynecologic origins are even rarer, share similar aggressive behavior and poor outcomes. We performed stranded paired-end RNA-seq of 13 samples, including 12 samples with matched whole exome sequencing (WES) data. Sites of origin for tumors in our cohort were the cervix (69%), ovary (19%), and endometrium (12%). The median number of prior lines of therapy was 1. Median PFS and OS were 1 and 12 months, respectively, indicating their highly lethal nature. Comparing transcriptomic profiles with TCGA cervical and ovarian cancers, chromatin assembly and nucleosome organization were the top GO functions for significantly over-expressed genes in our cohort. Remarkably, under-expressed genes in our cohort were enriched for protein modification and catabolic processes, and neutrophil-mediated immunity. Compared to small cell lung cancer (SCLC), our cohort showed highly distinct transcriptomic patterns, and represented the YAP1 high molecular subtype.

2021-09-01 | GSE157601 | GEO

Chromatin-informed inference of transcriptional programs in gynecologic cancers [ATAC-Seq]

Project description:Epigenomic data on transcription factor occupancy and chromatin accessibility can elucidate the developmental origin of cancer cells and reveal the enhancer landscape of key oncogenic transcriptional regulators. However, in many cancers, epigenomic analyses have been limited, and computational methods to infer regulatory networks in tumors typically use expression data alone, or rely on transcription factor (TF) motifs in annotated promoter regions. Here, we develop a novel machine learning strategy called PSIONIC (patient-specific inference of networks informed by chromatin) to combine cell line chromatin accessibility data with large tumor expression data sets and model the effect of enhancers on transcriptional programs in multiple cancers. We generated a new ATAC-seq data set profiling chromatin accessibility in gynecologic and basal breast cancer cell lines and applied PSIONIC to 723 RNA-seq experiments from ovarian, uterine, and basal breast tumors as well as 96 cell line RNA-seq profiles. Our computational framework enables us to share information across tumors to learn patient-specific inferred TF activities, revealing regulatory differences between and within tumor types. Many of the identified TF regulators were significantly associated with survival outcome in basal breast, uterine serous and endometrioid carcinomas. Moreover, PSIONIC-predicted activity for MTF1 in cell line models correlated with sensitivity to MTF1 inhibition. Therefore computationally dissecting the role of TFs in gynecologic cancers may ultimately advance personalized therapy.

2019-05-01 | GSE114964 | GEO

Gene expression profile of primary ovarian tumors and matched metastasis

Project description:Ovarian cancer is the most frequent cause of cancer death in women and the leading cause of death related to gynecological cancer, accounting for 5% of estimated cancer deaths. Due to its asymptomatic nature at early stages, most ovarian cancers were diagnosed at an advanced stage, with distant metastasis in the abdominal cavity. Cancer metastasis is the primary cause of morbidity, and contributes to 95% of cancer-related deaths. Metastatic ovarian cancer is closely related with recurrence and drug resistance, rendering metastasis as the major challenge in the course of ovarian cancer treatment. Thorough understanding of ovarian cancer metastasis is believed to contribute to improve cancer cure rates, while it is still not well elucidated. One important aspect of ovarian cancer metastasis research is the identification of driver molecular. To identify proteins required for ovarian cancer metastasis, we carried out unbiased high-throughput screening by comparing the expression profile of ovarian cancer primary and metastasis tissues.

2023-01-20 | GSE222982 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data