Scientists at the University of Illinois have used The Cancer Genome Atlas to pinpoint dozens of biomarkers that can gauge a patient's survival prospects with ovarian cancer and also predict when the cancer might return.
They identified 21 microRNAs tied to ovarian cancer. The team also spotted 838 genes and 12 transcription factors linked to ovarian cancer survival. Their new roster also includes dozens of biomarkers to help predict ovarian cancer recurrence--another 734 target genes and 8 transcription factors, the University of Illinois explained. These new predictive elements could help develop better and less invasive diagnostic tests down the line, the research team believes, and also offer a way to develop personalized treatments.
While more research is necessary, this would be a crucial advance for treating ovarian cancer, which is the fifth most common cause of cancer death in women in the U.S. Ovarian cancer is particularly hard to diagnose because it doesn't display clear symptoms, and the healthcare system also lacks definitive imaging or blood tests.
The Cancer Genome Atlas provided a treasure trove of data covering things including cancer treatment and tumor stage, cancer recurrence and ovarian cancer patients' age and survival rates. With data in hand, the scientists completed a series of statistical tests involving patient survival time and cancer recurrence, covering the months from a cancer diagnosis to when it returns. What's more, in addition to outlining ovarian cancer survival and its recurrence, they have also figured out how all the various biomarkers interact to affect survival and when the cancer comes back.
"This demonstrated that the consideration of networks of microRNAs, transcription factors and target genes allows us to identify reliable indicators of cancer survival and recurrence, and serves as the basis for effective prognostic tools," researcher Sandra Rodrigues-Zas, a University of Illinois animal sciences professor, told the university.
The journal PLoS ONE has published the team's research in detail.
- read the release
- here's the journal article