Identifying Genes Linked to Ovarian Cancer from Normal Ovarian Epithelium
Author Information
Author(s): Emmanuel Catherine, Gava Natalie, Kennedy Catherine, Balleine Rosemary L., Sharma Raghwa, Wain Gerard, Brand Alison, Hogg Russell, Etemadmoghadam Dariush, George Joshy, Birrer Michael J., Clarke Christine L., Chenevix-Trench Georgia, Bowtell David D. L., Harnett Paul R., deFazio Anna
Primary Institution: Department of Gynaecological Oncology, Westmead Hospital, Westmead, New South Wales, Australia
Hypothesis
A subset of genes involved in normal ovarian epithelial cell functions are also consistently aberrantly expressed in ovarian cancer.
Conclusion
The study identified 338 genes that are regulated during the estrous cycle and dysregulated in ovarian cancer, suggesting pathways and novel candidate genes that may contribute to ovarian cancer development.
Supporting Evidence
- 338 genes were identified that are regulated during the estrous cycle and dysregulated in ovarian cancer.
- Six of seven candidates selected for validation were expressed in serous ovarian cancer.
- Most genes were overexpressed in ovarian cancer compared to normal ovarian surface epithelium.
- Chromosome segregation emerged as an important process in which genes from the list were over-represented.
- Lower expression of NUAK2 was associated with shorter overall survival in ovarian cancer patients.
Takeaway
Scientists looked at genes in normal ovaries and found some that are also messed up in ovarian cancer, which could help us understand how the disease starts.
Methodology
The study involved gene expression analysis of murine ovarian surface epithelium during the estrous cycle and comparison with human ovarian cancer datasets.
Potential Biases
Potential bias in gene selection due to reliance on existing datasets.
Limitations
The study primarily focused on serous ovarian cancer and may not be generalizable to other types.
Participant Demographics
Cohort 1 included 20 serous ovarian cancer samples and 10 normal ovary samples; Cohort 2 included 96 serous ovarian cancer samples.
Statistical Information
P-Value
p<0.0001
Statistical Significance
p<0.0001
Digital Object Identifier (DOI)
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