Dataset Information

Evidence of a genetic link between endometriosis and ovarian cancer.

ABSTRACT:

Objective

To evaluate whether endometriosis-associated genetic variation affects risk of ovarian cancer.

Design

Pooled genetic analysis.

Setting

University hospital.

Patient(s)

Genetic data from 46,176 participants (15,361 ovarian cancer cases and 30,815 controls) from 41 ovarian cancer studies.

Intervention(s)

None.

Main outcome measure(s)

Endometriosis-associated genetic variation and ovarian cancer.

Result(s)

There was significant evidence of an association between endometriosis-related genetic variation and ovarian cancer risk, especially for the high-grade serous and clear cell histotypes. Overall we observed 15 significant burden statistics, which was three times more than expected.

Conclusion(s)

By focusing on candidate regions from a phenotype associated with ovarian cancer, we have shown a clear genetic link between endometriosis and ovarian cancer that warrants further follow-up. The functional significance of the identified regions and SNPs is presently uncertain, though future fine mapping and histotype-specific functional analyses may shed light on the etiologies of both gynecologic conditions.

SUBMITTER: Lee AW

PROVIDER: S-EPMC5068352 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Evidence of a genetic link between endometriosis and ovarian cancer.

Lee Alice W AW Templeman Claire C Stram Douglas A DA Beesley Jonathan J Tyrer Jonathan J Berchuck Andrew A Pharoah Paul P PP Chenevix-Trench Georgia G Pearce Celeste Leigh CL

Fertility and sterility 20151023 1

<h4>Objective</h4>To evaluate whether endometriosis-associated genetic variation affects risk of ovarian cancer.<h4>Design</h4>Pooled genetic analysis.<h4>Setting</h4>University hospital.<h4>Patient(s)</h4>Genetic data from 46,176 participants (15,361 ovarian cancer cases and 30,815 controls) from 41 ovarian cancer studies.<h4>Intervention(s)</h4>None.<h4>Main outcome measure(s)</h4>Endometriosis-associated genetic variation and ovarian cancer.<h4>Result(s)</h4>There was significant evidence of ...[more]

PMID: 26477498

Similar Datasets

Project description:AimEndometriosis is one of the most common reproductive system diseases, but the mechanisms of disease progression are still unclear. Due to its high recurrence rate, searching for potential therapeutic biomarkers involved in the pathogenesis of endometriosis is an urgent issue.MethodsDue to the similarities between endometriosis and ovarian cancer, four endometriosis datasets and one ovarian cancer dataset were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, followed by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) analyses. Then, we validated gene expression and performed survival analysis with ovarian serous cystadenocarcinoma (OV) datasets in TCGA/GTEx database, and searched for potential drugs in the Drug-Gene Interaction Database. Finally, we explored the miRNAs of key genes to find biomarkers associated with the recurrence of endometriosis.ResultsIn total, 104 DEGs were identified in the endometriosis datasets, and the main enriched GO functions included cell adhesion, extracellular exosome and actin binding. Fifty DEGs were identified between endometriosis and ovarian cancer datasets including 11 consistently regulated genes, and nine DEGs with significant expression in TCGA/GTEx. Only IGHM had both significant expression and an association with survival, three module DEGs and two significantly expressed DEGs had drug associations, and 10 DEGs had druggability.ConclusionsITGA7, ITGBL1 and SORBS1 may help us understand the invasive nature of endometriosis, and IGHM might be related to recurrence; moreover, these genes all may be potential therapeutic targets.KEY MESSAGEThis manuscript used a bioinformatics approach to find target genes for the treatment of endometriosis.This manuscript used a new approach to find target genes by drawing on common characteristics between ovarian cancer and endometriosis.We screened relevant therapeutic agents for target genes in the drug database, and performed histological validation of target genes with both expression and survival analysis difference in cancer databases.

Dataset Information

Evidence of a genetic link between endometriosis and ovarian cancer.

Objective

Design

Setting

Patient(s)

Intervention(s)

Main outcome measure(s)

Result(s)

Conclusion(s)

Publications

Evidence of a genetic link between endometriosis and ovarian cancer.

Similar Datasets

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