Scoring genes in ovarian cancer could predict treatment response

Ovarian cancer is often only diagnosed when it is quite advanced. The main treatment for advanced disease is surgery followed by highly toxic, platinum-based chemotherapy. But only 70% of women respond to it, so a biomarker that could pick out responders would stop unnecessary treatment and keep healthcare costs down.

Researchers from the Dana-Farber Cancer Institute have created a score based on the expression of genes involved in the repair of DNA after platinum-based treatment to see if this could predict the response, but the take on this is mixed.

The team used data from The Cancer Genome Atlas (TCGA), a huge depository of genetic information, focusing on DNA repair genes in ovarian cancer that were linked with survival, and used 23 genes to create a score described as low or high. High scores seemed to indicate improved survival and response to platinum-based treatment, and lower chances of progression or recurrence. Lower scores may suggest better responses to treatments that use different pathways. This idea has not yet been tested in clinical trials, but the researchers hope that, if the results were validated, the scoring scale could be used to direct patients towards the best treatments.

Ovarian cancer is the leading cause of gynecological cancer death and the fifth most common cause of cancer death overall in women in the U.S. An estimated 15,500 women could die from the disease in 2012. The accompanying editorial is interested but skeptical. It suggests that even though not all women respond to treatment, other options are only experimental, so the biomarker or biomarker panel would have to be highly predictive, and the results would need to be thoroughly validated. "The study… is an important effort in that direction but demonstrates the challenges we face as we attempt to utilize large datasets to develop personalized genomic medicines. The premature application of inadequately validated biomarkers may adversely impact the successful implementation of individualized therapies," the editorial concludes.

- see the paper in JNCI
- check out the editorial in JNCI
- read the article in CancerNetwork (reg. req.)

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