Scientists at A*STAR’s Institute of Medical Biology (IMB) have found new clues to early detection and precision treatment of ovarian cancer, currently one of the most difficult cancers to diagnose early due to the lack of symptoms that are unique to the illness.
There are three predominant cancers that affect women, breast, ovarian and womb cancer. Of the three, ovarian cancer is of the greatest concern as it is usually diagnosed only at an advanced stage due to the absence of clear early warning symptoms. Successful treatment is difficult at this late stage, resulting in high mortality rates. Ovarian cancer has increased in prevalence in Singapore as well as other developed countries recently. It is now the fifth most common cancer in Singapore amongst women, with about 280 cases diagnosed annually and 90 deaths per year.
The team have identified a molecule, known as Lgr5, on a subset of cells in the ovarian surface epithelium. Lgr5 has been previously used to identify stem cells in other tissues including the intestine and stomach, but this is the first time that scientists have successfully located this important biomarker in the ovary. 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 earlier, allowing for more effective treatment at an early stage of the illness.
Of the different types of ovarian cancers detected, high-grade serous ovarian carcinoma (HG-SOC) is the most prevalent of epithelial ovarian cancers. It has also proven to be one of the most lethal ovarian cancers, with only 30 per cent of such patients surviving more than five years after diagnosis. HG-SOC remains poorly understood, with a lack of biomarkers identified for clinical use, from diagnosis to prognosis of patient survival rates.
By applying bioinformatics analysis on big cancer genomics data, the team were able to identify genes whose mutation status could be used for prognosis and development of personalized treatment for HG-SOC.
The gene, Checkpoint Kinase 2 (CHEK2), has been identified as an effective prognostic marker of patient survival. 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. The previous opensource study was published in Cell Cycle.
Mortality after diagnosis currently remains high, as patients receive similar treatment options of chemotherapy and radiotherapy despite the diverse nature of tumour cells within tumours and across different tumour samples. With these findings, personalised medicine for ovarian cancer could be developed, with targeted treatment that would be optimised for subgroups of patients.
The team is now studying the mechanisms of how Lgr5-expressing stem cells regenerate in normal tissue. The regenerative ability of Lgr5-expressing stem cells makes them potentially useful for therapies that require tissue repair or replacement, such as through gene therapy to tackle ovary defects.
By using Lgr-5 as a biomarker to isolate and purify normal ovary stem cells and ovarian cancer stem cells, scientists can now compare normal and cancerous cells to identify differences between them. Such differences may then represent new therapeutic targets for ovarian cancer treatment.
The medical community have been intensively looking for markers of ovary stem cells for decades, and the identification of Lgr5 as a specific marker of these cells represents a major breakthrough in this field. Researchers can now rigorously investigate whether these stem cells are the origin of human ovarian cancer, and if so, how to target and eradicate them. This finding has paved the way for the development of cancer therapeutics in the future.
The team are excited by these findings as they may open up new possibilities for ovarian cancer treatment. This beautiful and meticulous study has led to a breakthrough discovery in a very challenging field.
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