Protein Markers Help Predict Ovarian Cancer Recurrence

August 30, 2013

A new index using protein markers can identify ovarian cancer cases at high and low risk for recurrence and discriminate between short- and long-term survivors.

A PRotein-driven index of OVARian cancer (PROVAR) developed using reverse-phase protein arrays can significantly discriminate between ovarian cancer cases at high risk and low risk of recurrence and between short-term and long-term survivors, according to the findings of a new study that used data generated from The Cancer Genome Atlas pilot program.1

For the study, researchers used reverse-phase protein arrays to generate ovarian carcinoma protein expression profiles on 412 cases. The researchers then evaluated whether these profiles, which were developed using PROVAR, could help predict which avenue of therapy would provide the best patient outcomes. Because tumor recurrence is common in patients with ovarian cancer, it is important that the initial treatment be as targeted as possible to help minimize the odds of tumor recurrence.

In an independent cohort of 226 cases of high-grade serous ovarian carcinomas, PROVAR significantly discriminated these cases into groups at high risk and at low risk for tumor recurrence. Researchers were also able to identify short-term and long-term survivors using PROVAR based on the identification of 9 protein markers that helped predict time to recurrence (n=222). An additional finding was that the protein-based PROVAR was able to predict tumor progression significantly better than gene expression–based outcome classification models. The study authors suggest that identification of protein markers associated with disease recurrence may provide insights into tumor biology, especially when combined with other features associated with outcome, such as BRCA mutation.

Currently, no targeted therapies have been approved for ovarian cancer treatment. However, the researchers suggested that patients identified as high risk for early recurrence may benefit from dose-density chemotherapy or a combination of taxane, platinum, and bevacizumab, which may cause more treatment-related adverse effects but are potentially more effective than the standard platinum-based chemotherapy.

These findings illustrate the potential of protein-driven treatment response predictions, the researchers wrote. Validation of PROVAR in a prospective setting is needed before it can be recommended for clinical use.

“In the era of personalized medicine, identification of patients at high risk of early recurrence may provide clinicians with opportunities for early interference and positively impact survival for a group of patients in dire need of improved prospects,” the study authors concluded.1

References:

1. Yang JY, Yoshihara K, Tanaka K, et al. Predicting time to ovarian carcinoma recurrence using protein markers. J Clin Invest. 2013 Aug 15. DOI: 10.1171/JCI68509. [Epub ahead of print]