Title
Using Data from the Cancer Genome Atlas to Investigate Molecular Events Related to Ovarian Cancer
Abstract
Ovarian Cancer is the most lethal gynecologic malignancy. Analyzing the molecular events related to ovarian cancer helps understand the pathogenesis of ovarian cancer from a genetic point of view. As miRNA singletons have been found significantly related to ovarian cancer and many other cancers, miRNAs have been recognized as an important riboregulator of gene expression. However, little is known about how pairs of miRNA expression profiles associate with ovarian cancer. In our analysis, we explored the combinatorial effects of miRNA pairs on regulating gene expression. We assessed the non-additive interaction between miRNA pairs on gene expression of patients that carry high grade ovarian cancer. We demonstrate how different miRNAs collectively contribute to ovarian cancer. We will illustrate two examples of miRNA pairs, hsa.miR.937 & hsa.let.7b and hsa.miR.1277& hsa.miR.485.3b, that we found exhibit non-additive interaction pattern on affecting gene expression of the patients with high grade Ovarian Cancer.
Description
Additional contributors: Gang Fang; Michael Steinbach (faculty mentor)
Funding information
This research was supported by the Undergraduate Research Opportunities Program (UROP).
Suggested Citation
Liu, Xiaoye.
(2011).
Using Data from the Cancer Genome Atlas to Investigate Molecular Events Related to Ovarian Cancer.
Retrieved from the University of Minnesota Digital Conservancy,
https://hdl.handle.net/11299/117625.