New Technology Helping Women With Ovarian cancer are among the most difficult cancers to diagnose and treat. There are no early stage diagnostics for this disorder and by the time they are discovered, they may not respond to standard cancer treatments.
Ovarian cancer The molecule Lgr5 is present in the ovarian surface epithelium. While it has been found to be present in the stem cells of other tissues such as intestine and stomach, this is the first time that scientists have located it in the ovary. Lgr5 was found to be produced by an important subset of epithelial cells that control the development of the ovary. Using Lgr5 as a biomarker of ovarian stem cells, this disorder can potentially be detected earlier, allowing for more effective treatment at an early stage of the illness.
In doing so, they have unearthed a new population of epithelial stem cells in the ovary which produce Lgr5 and control the development of the ovary. Using Lgr5 as a biomarker of ovarian stem cells, ovarian cancer can potentially be detected and thus treated at an earlier stage.
Personalized treatment with the help of bioinformatics analysis
Currently more than 30 types of ovarian cancers have been known to affect women, and of these high-grade serous ovarian carcinoma (HG-SOC) is the most prevalent of type. The prognosis for this type of cancer is also very bleak with only 30 per cent of patients surviving more than five years after diagnosis. Again, the lack of biomarkers for early detection makes this a poorly understood illness.
Ovarian cancer Scientists in the current study found that HG-SOC patients with mutations in this gene succumbed to the disease within five years of diagnosis, possibly because CHEK2 mutations were associated with poor response to existing cancer therapies. These findings were published in Cell Cycle in July 2014.
Ovarian cancer Mortality after diagnosis currently remains high, as patients receive similar treatment options of chemotherapy and radiotherapy despite the diverse nature of tumor cells within tumors and across different tumor samples.
The scientists hope that with the new findings, personalized medicine and targeted treatments can be developed to treat subgroups of ovarian cancer patients.